Overview

Dataset statistics

Number of variables81
Number of observations1000
Missing cells16458
Missing cells (%)20.3%
Total size in memory5.1 MiB
Average record size in memory5.2 KiB

Variable types

Numeric1
Text74
Unsupported6

Alerts

building_type has constant value ""Constant
no_good_check has constant value ""Constant
amount_due has constant value ""Constant
electrical_permit_number has 545 (54.5%) missing valuesMissing
associatedjobnumber has 835 (83.5%) missing valuesMissing
plan_examiner_assigned_date has 52 (5.2%) missing valuesMissing
incomplete_date has 1000 (100.0%) missing valuesMissing
last_incomplete_submission has 1000 (100.0%) missing valuesMissing
first_objection_date has 754 (75.4%) missing valuesMissing
last_objection_date has 754 (75.4%) missing valuesMissing
resubmission_date has 757 (75.7%) missing valuesMissing
permit_entire_date has 158 (15.8%) missing valuesMissing
signedoff_date has 313 (31.3%) missing valuesMissing
applicant_address has 755 (75.5%) missing valuesMissing
designprofessional_firstname has 345 (34.5%) missing valuesMissing
designprofessional_lastname has 345 (34.5%) missing valuesMissing
designprofessional has 345 (34.5%) missing valuesMissing
designprofessional_address has 344 (34.4%) missing valuesMissing
designprofessional_city has 344 (34.4%) missing valuesMissing
designprofessional_state has 344 (34.4%) missing valuesMissing
designprofessional_zip has 344 (34.4%) missing valuesMissing
designprofessional_license has 344 (34.4%) missing valuesMissing
owner_title has 779 (77.9%) missing valuesMissing
owner_address has 1000 (100.0%) missing valuesMissing
owner_city has 1000 (100.0%) missing valuesMissing
owner_state has 1000 (100.0%) missing valuesMissing
owner_zip has 1000 (100.0%) missing valuesMissing
depacp5controlno has 988 (98.8%) missing valuesMissing
no_good_check has 988 (98.8%) missing valuesMissing
0 has unique valuesUnique
job_filing_number has unique valuesUnique
incomplete_date is an unsupported type, check if it needs cleaning or further analysisUnsupported
last_incomplete_submission is an unsupported type, check if it needs cleaning or further analysisUnsupported
owner_address is an unsupported type, check if it needs cleaning or further analysisUnsupported
owner_city is an unsupported type, check if it needs cleaning or further analysisUnsupported
owner_state is an unsupported type, check if it needs cleaning or further analysisUnsupported
owner_zip is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 22:30:35.031295
Analysis finished2023-12-09 22:30:38.379443
Duration3.35 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-09T22:30:38.517267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.8194361
Coefficient of variation (CV)0.5770618104
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.66667
MonotonicityStrictly increasing
2023-12-09T22:30:38.695926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
672 1
 
0.1%
659 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
662 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
ValueCountFrequency (%)
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%

job_filing_number
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
2023-12-09T22:30:39.040448image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12000
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st rowB00817943-I1
2nd rowM00663451-I1
3rd rowQ00801503-I1
4th rowQ00288123-I1
5th rowM00159103-I1
ValueCountFrequency (%)
m00553623-i1 1
 
0.1%
m00069893-i1 1
 
0.1%
m00200916-i1 1
 
0.1%
b00515880-i1 1
 
0.1%
x00210686-p1 1
 
0.1%
m00856083-i1 1
 
0.1%
m00475827-i1 1
 
0.1%
b00512155-i1 1
 
0.1%
m00108475-p3 1
 
0.1%
m00156960-i1 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T22:30:39.521454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2613
21.8%
1 1642
13.7%
- 1000
 
8.3%
I 839
 
7.0%
2 733
 
6.1%
3 643
 
5.4%
M 615
 
5.1%
8 588
 
4.9%
5 576
 
4.8%
7 562
 
4.7%
Other values (9) 2189
18.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9000
75.0%
Uppercase Letter 2000
 
16.7%
Dash Punctuation 1000
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2613
29.0%
1 1642
18.2%
2 733
 
8.1%
3 643
 
7.1%
8 588
 
6.5%
5 576
 
6.4%
7 562
 
6.2%
6 559
 
6.2%
4 553
 
6.1%
9 531
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
I 839
41.9%
M 615
30.8%
B 181
 
9.0%
P 153
 
7.6%
Q 111
 
5.5%
X 86
 
4.3%
S 12
 
0.6%
Z 3
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10000
83.3%
Latin 2000
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2613
26.1%
1 1642
16.4%
- 1000
 
10.0%
2 733
 
7.3%
3 643
 
6.4%
8 588
 
5.9%
5 576
 
5.8%
7 562
 
5.6%
6 559
 
5.6%
4 553
 
5.5%
Latin
ValueCountFrequency (%)
I 839
41.9%
M 615
30.8%
B 181
 
9.0%
P 153
 
7.6%
Q 111
 
5.5%
X 86
 
4.3%
S 12
 
0.6%
Z 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2613
21.8%
1 1642
13.7%
- 1000
 
8.3%
I 839
 
7.0%
2 733
 
6.1%
3 643
 
5.4%
M 615
 
5.1%
8 588
 
4.9%
5 576
 
4.8%
7 562
 
4.7%
Other values (9) 2189
18.2%
Distinct979
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size64.6 KiB
2023-12-09T22:30:39.921627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9000
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique958 ?
Unique (%)95.8%

Sample

1st rowB00817943
2nd rowM00663451
3rd rowQ00801503
4th rowQ00288123
5th rowM00159103
ValueCountFrequency (%)
m00309436 2
 
0.2%
m00213890 2
 
0.2%
m00477243 2
 
0.2%
m00473712 2
 
0.2%
m00422187 2
 
0.2%
q00754956 2
 
0.2%
m00555342 2
 
0.2%
b00843293 2
 
0.2%
m00593637 2
 
0.2%
m00263893 2
 
0.2%
Other values (969) 980
98.0%
2023-12-09T22:30:40.449399image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2613
29.0%
2 702
 
7.8%
1 696
 
7.7%
3 629
 
7.0%
M 615
 
6.8%
8 588
 
6.5%
5 576
 
6.4%
7 562
 
6.2%
6 556
 
6.2%
4 548
 
6.1%
Other values (5) 915
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8000
88.9%
Uppercase Letter 1000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2613
32.7%
2 702
 
8.8%
1 696
 
8.7%
3 629
 
7.9%
8 588
 
7.3%
5 576
 
7.2%
7 562
 
7.0%
6 556
 
7.0%
4 548
 
6.9%
9 530
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
M 615
61.5%
B 181
 
18.1%
Q 111
 
11.1%
X 86
 
8.6%
S 7
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 8000
88.9%
Latin 1000
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2613
32.7%
2 702
 
8.8%
1 696
 
8.7%
3 629
 
7.9%
8 588
 
7.3%
5 576
 
7.2%
7 562
 
7.0%
6 556
 
7.0%
4 548
 
6.9%
9 530
 
6.6%
Latin
ValueCountFrequency (%)
M 615
61.5%
B 181
 
18.1%
Q 111
 
11.1%
X 86
 
8.6%
S 7
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2613
29.0%
2 702
 
7.8%
1 696
 
7.7%
3 629
 
7.0%
M 615
 
6.8%
8 588
 
6.5%
5 576
 
6.4%
7 562
 
6.2%
6 556
 
6.2%
4 548
 
6.1%
Other values (5) 915
 
10.2%
Distinct12
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T22:30:40.601074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.5%

Sample

1st rowI1
2nd rowI1
3rd rowI1
4th rowI1
5th rowI1
ValueCountFrequency (%)
i1 839
83.9%
p1 106
 
10.6%
p2 30
 
3.0%
p3 13
 
1.3%
p4 3
 
0.3%
s4 2
 
0.2%
s6 2
 
0.2%
p6 1
 
0.1%
z1 1
 
0.1%
s9 1
 
0.1%
Other values (2) 2
 
0.2%
2023-12-09T22:30:40.853559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 946
47.3%
I 839
41.9%
P 153
 
7.6%
2 31
 
1.6%
3 14
 
0.7%
4 5
 
0.2%
S 5
 
0.2%
6 3
 
0.1%
Z 3
 
0.1%
9 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
50.0%
Uppercase Letter 1000
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 946
94.6%
2 31
 
3.1%
3 14
 
1.4%
4 5
 
0.5%
6 3
 
0.3%
9 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
I 839
83.9%
P 153
 
15.3%
S 5
 
0.5%
Z 3
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
50.0%
Latin 1000
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 946
94.6%
2 31
 
3.1%
3 14
 
1.4%
4 5
 
0.5%
6 3
 
0.3%
9 1
 
0.1%
Latin
ValueCountFrequency (%)
I 839
83.9%
P 153
 
15.3%
S 5
 
0.5%
Z 3
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 946
47.3%
I 839
41.9%
P 153
 
7.6%
2 31
 
1.6%
3 14
 
0.7%
4 5
 
0.2%
S 5
 
0.2%
6 3
 
0.1%
Z 3
 
0.1%
9 1
 
< 0.1%
Distinct660
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T22:30:41.121305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique422 ?
Unique (%)42.2%

Sample

1st row2023-02-15T00:00:00.000
2nd row2022-02-01T00:00:00.000
3rd row2023-02-08T00:00:00.000
4th row2020-02-05T00:00:00.000
5th row2019-06-05T00:00:00.000
ValueCountFrequency (%)
2019-06-05t00:00:00.000 7
 
0.7%
2019-05-02t00:00:00.000 6
 
0.6%
2019-12-26t00:00:00.000 5
 
0.5%
2019-08-05t00:00:00.000 5
 
0.5%
2019-08-15t00:00:00.000 5
 
0.5%
2019-11-20t00:00:00.000 4
 
0.4%
2019-09-05t00:00:00.000 4
 
0.4%
2019-06-19t00:00:00.000 4
 
0.4%
2019-01-24t00:00:00.000 4
 
0.4%
2019-12-03t00:00:00.000 4
 
0.4%
Other values (650) 952
95.2%
2023-12-09T22:30:41.521339image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11434
49.7%
2 2264
 
9.8%
- 2000
 
8.7%
: 2000
 
8.7%
1 1430
 
6.2%
T 1000
 
4.3%
. 1000
 
4.3%
9 484
 
2.1%
3 354
 
1.5%
8 293
 
1.3%
Other values (4) 741
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11434
67.3%
2 2264
 
13.3%
1 1430
 
8.4%
9 484
 
2.8%
3 354
 
2.1%
8 293
 
1.7%
6 189
 
1.1%
4 189
 
1.1%
5 183
 
1.1%
7 180
 
1.1%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11434
52.0%
2 2264
 
10.3%
- 2000
 
9.1%
: 2000
 
9.1%
1 1430
 
6.5%
. 1000
 
4.5%
9 484
 
2.2%
3 354
 
1.6%
8 293
 
1.3%
6 189
 
0.9%
Other values (3) 552
 
2.5%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11434
49.7%
2 2264
 
9.8%
- 2000
 
8.7%
: 2000
 
8.7%
1 1430
 
6.2%
T 1000
 
4.3%
. 1000
 
4.3%
9 484
 
2.1%
3 354
 
1.5%
8 293
 
1.3%
Other values (4) 741
 
3.2%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size64.6 KiB
2023-12-09T22:30:41.694681image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length17
Median length10
Mean length8.985
Min length3

Characters and Unicode

Total characters8985
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNew Filing
2nd rowNew Filing
3rd rowNew Filing
4th rowNew Filing
5th rowNew Filing
ValueCountFrequency (%)
filing 847
45.9%
new 839
45.4%
paa 153
 
8.3%
subsequent 8
 
0.4%
2023-12-09T22:30:41.983523image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1694
18.9%
n 855
9.5%
e 855
9.5%
g 847
9.4%
847
9.4%
F 847
9.4%
l 847
9.4%
N 839
9.3%
w 839
9.3%
A 306
 
3.4%
Other values (7) 209
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5985
66.6%
Uppercase Letter 2153
 
24.0%
Space Separator 847
 
9.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1694
28.3%
n 855
14.3%
e 855
14.3%
g 847
14.2%
l 847
14.2%
w 839
14.0%
u 16
 
0.3%
b 8
 
0.1%
s 8
 
0.1%
q 8
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
F 847
39.3%
N 839
39.0%
A 306
 
14.2%
P 153
 
7.1%
S 8
 
0.4%
Space Separator
ValueCountFrequency (%)
847
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8138
90.6%
Common 847
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1694
20.8%
n 855
10.5%
e 855
10.5%
g 847
10.4%
F 847
10.4%
l 847
10.4%
N 839
10.3%
w 839
10.3%
A 306
 
3.8%
P 153
 
1.9%
Other values (6) 56
 
0.7%
Common
ValueCountFrequency (%)
847
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8985
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1694
18.9%
n 855
9.5%
e 855
9.5%
g 847
9.4%
847
9.4%
F 847
9.4%
l 847
9.4%
N 839
9.3%
w 839
9.3%
A 306
 
3.4%
Other values (7) 209
 
2.3%
Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size65.0 KiB
2023-12-09T22:30:42.160235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length8
Mean length9.466
Min length8

Characters and Unicode

Total characters9466
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowElevator
2nd rowElevator
3rd rowElevator
4th rowElevator
5th rowElevator
ValueCountFrequency (%)
elevator 785
67.3%
accessibility 83
 
7.1%
lift 83
 
7.1%
personnel 83
 
7.1%
hoist 83
 
7.1%
dumbwaiter 22
 
1.9%
conveyor 16
 
1.4%
escalator 11
 
0.9%
2023-12-09T22:30:42.459179image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1072
11.3%
t 1067
11.3%
o 994
10.5%
l 962
10.2%
r 917
9.7%
a 829
8.8%
v 801
8.5%
E 796
8.4%
i 437
 
4.6%
s 343
 
3.6%
Other values (15) 1248
13.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8134
85.9%
Uppercase Letter 1166
 
12.3%
Space Separator 166
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1072
13.2%
t 1067
13.1%
o 994
12.2%
l 962
11.8%
r 917
11.3%
a 829
10.2%
v 801
9.8%
i 437
5.4%
s 343
 
4.2%
n 182
 
2.2%
Other values (7) 530
6.5%
Uppercase Letter
ValueCountFrequency (%)
E 796
68.3%
L 83
 
7.1%
P 83
 
7.1%
A 83
 
7.1%
H 83
 
7.1%
D 22
 
1.9%
C 16
 
1.4%
Space Separator
ValueCountFrequency (%)
166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9300
98.2%
Common 166
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1072
11.5%
t 1067
11.5%
o 994
10.7%
l 962
10.3%
r 917
9.9%
a 829
8.9%
v 801
8.6%
E 796
8.6%
i 437
4.7%
s 343
 
3.7%
Other values (14) 1082
11.6%
Common
ValueCountFrequency (%)
166
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1072
11.3%
t 1067
11.3%
o 994
10.5%
l 962
10.2%
r 917
9.7%
a 829
8.8%
v 801
8.5%
E 796
8.4%
i 437
 
4.6%
s 343
 
3.6%
Other values (15) 1248
13.2%
Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.0 KiB
2023-12-09T22:30:42.651114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length26
Median length10
Mean length10.429
Min length8

Characters and Unicode

Total characters10429
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSign Off Request Initiated
2nd rowSigned Off
3rd rowSigned Off
4th rowSign Off Request Initiated
5th rowSigned Off
ValueCountFrequency (%)
off 709
37.7%
signed 687
36.5%
approved 152
 
8.1%
permit 129
 
6.9%
entire 129
 
6.9%
sign 22
 
1.2%
request 22
 
1.2%
initiated 22
 
1.2%
withdrawn 6
 
0.3%
objections 4
 
0.2%
2023-12-09T22:30:42.980898image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 1418
13.6%
e 1167
11.2%
i 1021
9.8%
882
8.5%
n 870
8.3%
d 867
8.3%
O 713
6.8%
S 709
6.8%
g 709
6.8%
r 416
 
4.0%
Other values (20) 1657
15.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7665
73.5%
Uppercase Letter 1882
 
18.0%
Space Separator 882
 
8.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
f 1418
18.5%
e 1167
15.2%
i 1021
13.3%
n 870
11.4%
d 867
11.3%
g 709
9.2%
r 416
 
5.4%
t 334
 
4.4%
p 304
 
4.0%
o 156
 
2.0%
Other values (11) 403
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
O 713
37.9%
S 709
37.7%
A 152
 
8.1%
E 129
 
6.9%
P 129
 
6.9%
R 22
 
1.2%
I 22
 
1.2%
W 6
 
0.3%
Space Separator
ValueCountFrequency (%)
882
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9547
91.5%
Common 882
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
f 1418
14.9%
e 1167
12.2%
i 1021
10.7%
n 870
9.1%
d 867
9.1%
O 713
7.5%
S 709
7.4%
g 709
7.4%
r 416
 
4.4%
t 334
 
3.5%
Other values (19) 1323
13.9%
Common
ValueCountFrequency (%)
882
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10429
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 1418
13.6%
e 1167
11.2%
i 1021
9.8%
882
8.5%
n 870
8.3%
d 867
8.3%
O 713
6.8%
S 709
6.8%
g 709
6.8%
r 416
 
4.0%
Other values (20) 1657
15.9%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size74.8 KiB
2023-12-09T22:30:43.187447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length22
Median length22
Mean length19.467
Min length6

Characters and Unicode

Total characters19467
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAlteration/Replacement
2nd rowNew Installation
3rd rowAlteration/Replacement
4th rowAlteration/Replacement
5th rowAlteration/Replacement
ValueCountFrequency (%)
alteration/replacement 617
45.4%
new 358
26.4%
installation 358
26.4%
remove 20
 
1.5%
dismantle 5
 
0.4%
2023-12-09T22:30:43.540631image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2871
14.7%
t 2572
13.2%
a 1955
10.0%
n 1955
10.0%
l 1955
10.0%
o 995
 
5.1%
i 980
 
5.0%
m 642
 
3.3%
R 637
 
3.3%
p 617
 
3.2%
Other values (11) 4288
22.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16517
84.8%
Uppercase Letter 1975
 
10.1%
Other Punctuation 617
 
3.2%
Space Separator 358
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2871
17.4%
t 2572
15.6%
a 1955
11.8%
n 1955
11.8%
l 1955
11.8%
o 995
 
6.0%
i 980
 
5.9%
m 642
 
3.9%
p 617
 
3.7%
c 617
 
3.7%
Other values (4) 1358
8.2%
Uppercase Letter
ValueCountFrequency (%)
R 637
32.3%
A 617
31.2%
N 358
18.1%
I 358
18.1%
D 5
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 617
100.0%
Space Separator
ValueCountFrequency (%)
358
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18492
95.0%
Common 975
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2871
15.5%
t 2572
13.9%
a 1955
10.6%
n 1955
10.6%
l 1955
10.6%
o 995
 
5.4%
i 980
 
5.3%
m 642
 
3.5%
R 637
 
3.4%
p 617
 
3.3%
Other values (9) 3313
17.9%
Common
ValueCountFrequency (%)
/ 617
63.3%
358
36.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2871
14.7%
t 2572
13.2%
a 1955
10.0%
n 1955
10.0%
l 1955
10.0%
o 995
 
5.1%
i 980
 
5.0%
m 642
 
3.3%
R 637
 
3.3%
p 617
 
3.2%
Other values (11) 4288
22.0%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size59.7 KiB
2023-12-09T22:30:43.688045image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4000
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2014
3rd row2022
4th row2014
5th row1968
ValueCountFrequency (%)
1968 523
52.3%
2014 328
32.8%
2022 95
 
9.5%
2008 54
 
5.4%
2023-12-09T22:30:43.957687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 851
21.3%
2 667
16.7%
8 577
14.4%
0 531
13.3%
9 523
13.1%
6 523
13.1%
4 328
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 851
21.3%
2 667
16.7%
8 577
14.4%
0 531
13.3%
9 523
13.1%
6 523
13.1%
4 328
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 851
21.3%
2 667
16.7%
8 577
14.4%
0 531
13.3%
9 523
13.1%
6 523
13.1%
4 328
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 851
21.3%
2 667
16.7%
8 577
14.4%
0 531
13.3%
9 523
13.1%
6 523
13.1%
4 328
 
8.2%
Distinct426
Distinct (%)93.6%
Missing545
Missing (%)54.5%
Memory size49.1 KiB
2023-12-09T22:30:44.262679image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length15
Median length15
Mean length14.87692308
Min length7

Characters and Unicode

Total characters6769
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique399 ?
Unique (%)87.7%

Sample

1st rowM00659589-I1-EL
2nd rowm00507138-i1-el
3rd rowB00891574-I1-EL
4th rowB00086997-I1-EL
5th rowM00747979-I1-EL
ValueCountFrequency (%)
b00747910-i1-el 5
 
1.1%
m00314208-i1-el 4
 
0.9%
m00420245-i1-el 2
 
0.4%
m00151058-i1-el 2
 
0.4%
x00133846-i1-el 2
 
0.4%
m00485945-i1-el 2
 
0.4%
q00097961-i1-el 2
 
0.4%
m00583807-i1-el 2
 
0.4%
b00220415-i1-el 2
 
0.4%
m00380172-i1-el 2
 
0.4%
Other values (413) 430
94.5%
2023-12-09T22:30:44.710786image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1191
17.6%
- 896
13.2%
1 747
11.0%
E 333
 
4.9%
I 332
 
4.9%
L 331
 
4.9%
8 303
 
4.5%
2 293
 
4.3%
9 275
 
4.1%
5 261
 
3.9%
Other values (17) 1807
26.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4074
60.2%
Uppercase Letter 1328
 
19.6%
Dash Punctuation 896
 
13.2%
Lowercase Letter 471
 
7.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1191
29.2%
1 747
18.3%
8 303
 
7.4%
2 293
 
7.2%
9 275
 
6.8%
5 261
 
6.4%
4 257
 
6.3%
7 254
 
6.2%
3 249
 
6.1%
6 244
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
E 333
25.1%
I 332
25.0%
L 331
24.9%
M 180
13.6%
B 78
 
5.9%
Q 47
 
3.5%
X 25
 
1.9%
S 2
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
l 117
24.8%
e 115
24.4%
i 111
23.6%
m 61
13.0%
b 28
 
5.9%
x 20
 
4.2%
q 12
 
2.5%
s 7
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 896
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4970
73.4%
Latin 1799
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 333
18.5%
I 332
18.5%
L 331
18.4%
M 180
10.0%
l 117
 
6.5%
e 115
 
6.4%
i 111
 
6.2%
B 78
 
4.3%
m 61
 
3.4%
Q 47
 
2.6%
Other values (6) 94
 
5.2%
Common
ValueCountFrequency (%)
0 1191
24.0%
- 896
18.0%
1 747
15.0%
8 303
 
6.1%
2 293
 
5.9%
9 275
 
5.5%
5 261
 
5.3%
4 257
 
5.2%
7 254
 
5.1%
3 249
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6769
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1191
17.6%
- 896
13.2%
1 747
11.0%
E 333
 
4.9%
I 332
 
4.9%
L 331
 
4.9%
8 303
 
4.5%
2 293
 
4.3%
9 275
 
4.1%
5 261
 
3.9%
Other values (17) 1807
26.7%

bin
Text

Distinct843
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Memory size62.6 KiB
2023-12-09T22:30:45.125236image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique741 ?
Unique (%)74.1%

Sample

1st row3397939
2nd row1015862
3rd row4005201
4th row4042758
5th row1044166
ValueCountFrequency (%)
1076262 9
 
0.9%
1089694 8
 
0.8%
1036460 7
 
0.7%
1090274 6
 
0.6%
3427349 5
 
0.5%
1084306 4
 
0.4%
1036223 4
 
0.4%
1083869 4
 
0.4%
1077363 4
 
0.4%
1023157 4
 
0.4%
Other values (833) 945
94.5%
2023-12-09T22:30:45.648528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1345
19.2%
1 1205
17.2%
3 702
10.0%
2 627
9.0%
4 608
8.7%
8 546
7.8%
6 535
 
7.6%
7 503
 
7.2%
9 472
 
6.7%
5 457
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1345
19.2%
1 1205
17.2%
3 702
10.0%
2 627
9.0%
4 608
8.7%
8 546
7.8%
6 535
 
7.6%
7 503
 
7.2%
9 472
 
6.7%
5 457
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
Common 7000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1345
19.2%
1 1205
17.2%
3 702
10.0%
2 627
9.0%
4 608
8.7%
8 546
7.8%
6 535
 
7.6%
7 503
 
7.2%
9 472
 
6.7%
5 457
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1345
19.2%
1 1205
17.2%
3 702
10.0%
2 627
9.0%
4 608
8.7%
8 546
7.8%
6 535
 
7.6%
7 503
 
7.2%
9 472
 
6.7%
5 457
 
6.5%
Distinct641
Distinct (%)64.1%
Missing0
Missing (%)0.0%
Memory size59.0 KiB
2023-12-09T22:30:46.145576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.242
Min length1

Characters and Unicode

Total characters3242
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique467 ?
Unique (%)46.7%

Sample

1st row599
2nd row350
3rd row43-24
4th row107-02
5th row211
ValueCountFrequency (%)
100 14
 
1.4%
401 10
 
1.0%
30 9
 
0.9%
341 9
 
0.9%
55 8
 
0.8%
200 8
 
0.8%
1 8
 
0.8%
2 7
 
0.7%
10 7
 
0.7%
15 7
 
0.7%
Other values (632) 915
91.3%
2023-12-09T22:30:46.783307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 615
19.0%
0 434
13.4%
2 396
12.2%
3 348
10.7%
5 334
10.3%
4 259
8.0%
6 220
 
6.8%
7 182
 
5.6%
8 168
 
5.2%
9 167
 
5.2%
Other values (8) 119
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3123
96.3%
Dash Punctuation 108
 
3.3%
Lowercase Letter 7
 
0.2%
Space Separator 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 615
19.7%
0 434
13.9%
2 396
12.7%
3 348
11.1%
5 334
10.7%
4 259
8.3%
6 220
 
7.0%
7 182
 
5.8%
8 168
 
5.4%
9 167
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
i 2
28.6%
r 2
28.6%
o 1
14.3%
n 1
14.3%
e 1
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3233
99.7%
Latin 9
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 615
19.0%
0 434
13.4%
2 396
12.2%
3 348
10.8%
5 334
10.3%
4 259
8.0%
6 220
 
6.8%
7 182
 
5.6%
8 168
 
5.2%
9 167
 
5.2%
Other values (2) 110
 
3.4%
Latin
ValueCountFrequency (%)
A 2
22.2%
i 2
22.2%
r 2
22.2%
o 1
11.1%
n 1
11.1%
e 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 615
19.0%
0 434
13.4%
2 396
12.2%
3 348
10.7%
5 334
10.3%
4 259
8.0%
6 220
 
6.8%
7 182
 
5.6%
8 168
 
5.2%
9 167
 
5.2%
Other values (8) 119
 
3.7%
Distinct533
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size68.6 KiB
2023-12-09T22:30:47.179198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length26
Median length22
Mean length13.081
Min length6

Characters and Unicode

Total characters13081
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique365 ?
Unique (%)36.5%

Sample

1st rowWINTHROP STREET
2nd row5 AVENUE
3rd row21 STREET
4th rowNORTHERN BOULEVARD
5th rowEAST 78 STREET
ValueCountFrequency (%)
street 438
19.0%
avenue 384
 
16.7%
west 163
 
7.1%
east 126
 
5.5%
broadway 49
 
2.1%
park 39
 
1.7%
5 27
 
1.2%
boulevard 26
 
1.1%
3 20
 
0.9%
road 20
 
0.9%
Other values (413) 1010
43.9%
2023-12-09T22:30:47.748693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 2344
17.9%
1425
10.9%
T 1414
10.8%
A 1012
 
7.7%
S 944
 
7.2%
R 884
 
6.8%
N 722
 
5.5%
U 508
 
3.9%
V 461
 
3.5%
O 400
 
3.1%
Other values (28) 2967
22.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10804
82.6%
Space Separator 1425
 
10.9%
Decimal Number 851
 
6.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 2344
21.7%
T 1414
13.1%
A 1012
9.4%
S 944
8.7%
R 884
 
8.2%
N 722
 
6.7%
U 508
 
4.7%
V 461
 
4.3%
O 400
 
3.7%
W 289
 
2.7%
Other values (16) 1826
16.9%
Decimal Number
ValueCountFrequency (%)
1 168
19.7%
5 106
12.5%
3 101
11.9%
2 93
10.9%
4 78
9.2%
7 75
8.8%
6 72
8.5%
8 63
 
7.4%
0 53
 
6.2%
9 42
 
4.9%
Space Separator
ValueCountFrequency (%)
1425
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10804
82.6%
Common 2277
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 2344
21.7%
T 1414
13.1%
A 1012
9.4%
S 944
8.7%
R 884
 
8.2%
N 722
 
6.7%
U 508
 
4.7%
V 461
 
4.3%
O 400
 
3.7%
W 289
 
2.7%
Other values (16) 1826
16.9%
Common
ValueCountFrequency (%)
1425
62.6%
1 168
 
7.4%
5 106
 
4.7%
3 101
 
4.4%
2 93
 
4.1%
4 78
 
3.4%
7 75
 
3.3%
6 72
 
3.2%
8 63
 
2.8%
0 53
 
2.3%
Other values (2) 43
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13081
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 2344
17.9%
1425
10.9%
T 1414
10.8%
A 1012
 
7.7%
S 944
 
7.2%
R 884
 
6.8%
N 722
 
5.5%
U 508
 
3.9%
V 461
 
3.5%
O 400
 
3.1%
Other values (28) 2967
22.7%

zip
Text

Distinct141
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size60.7 KiB
2023-12-09T22:30:48.115043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)2.5%

Sample

1st row11203
2nd row10118
3rd row11101
4th row11368
5th row10075
ValueCountFrequency (%)
10019 44
 
4.4%
10001 41
 
4.1%
10022 39
 
3.9%
10036 39
 
3.9%
10011 33
 
3.3%
10017 32
 
3.2%
10003 26
 
2.6%
10012 23
 
2.3%
10023 19
 
1.9%
11201 18
 
1.8%
Other values (131) 686
68.6%
2023-12-09T22:30:48.604995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1801
36.0%
0 1537
30.7%
2 520
 
10.4%
3 289
 
5.8%
4 197
 
3.9%
6 175
 
3.5%
5 165
 
3.3%
7 133
 
2.7%
9 99
 
2.0%
8 84
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1801
36.0%
0 1537
30.7%
2 520
 
10.4%
3 289
 
5.8%
4 197
 
3.9%
6 175
 
3.5%
5 165
 
3.3%
7 133
 
2.7%
9 99
 
2.0%
8 84
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 5000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1801
36.0%
0 1537
30.7%
2 520
 
10.4%
3 289
 
5.8%
4 197
 
3.9%
6 175
 
3.5%
5 165
 
3.3%
7 133
 
2.7%
9 99
 
2.0%
8 84
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1801
36.0%
0 1537
30.7%
2 520
 
10.4%
3 289
 
5.8%
4 197
 
3.9%
6 175
 
3.5%
5 165
 
3.3%
7 133
 
2.7%
9 99
 
2.0%
8 84
 
1.7%
Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size63.8 KiB
2023-12-09T22:30:48.791379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.17
Min length5

Characters and Unicode

Total characters8170
Distinct characters19
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBROOKLYN
2nd rowMANHATTAN
3rd rowQUEENS
4th rowQUEENS
5th rowMANHATTAN
ValueCountFrequency (%)
manhattan 615
61.1%
brooklyn 181
 
18.0%
queens 111
 
11.0%
bronx 86
 
8.5%
staten 7
 
0.7%
island 7
 
0.7%
2023-12-09T22:30:49.118571image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1859
22.8%
N 1622
19.9%
T 1244
15.2%
M 615
 
7.5%
H 615
 
7.5%
O 448
 
5.5%
B 267
 
3.3%
R 267
 
3.3%
E 229
 
2.8%
L 188
 
2.3%
Other values (9) 816
10.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 8163
99.9%
Space Separator 7
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1859
22.8%
N 1622
19.9%
T 1244
15.2%
M 615
 
7.5%
H 615
 
7.5%
O 448
 
5.5%
B 267
 
3.3%
R 267
 
3.3%
E 229
 
2.8%
L 188
 
2.3%
Other values (8) 809
9.9%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8163
99.9%
Common 7
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1859
22.8%
N 1622
19.9%
T 1244
15.2%
M 615
 
7.5%
H 615
 
7.5%
O 448
 
5.5%
B 267
 
3.3%
R 267
 
3.3%
E 229
 
2.8%
L 188
 
2.3%
Other values (8) 809
9.9%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1859
22.8%
N 1622
19.9%
T 1244
15.2%
M 615
 
7.5%
H 615
 
7.5%
O 448
 
5.5%
B 267
 
3.3%
R 267
 
3.3%
E 229
 
2.8%
L 188
 
2.3%
Other values (9) 816
10.0%

block
Text

Distinct699
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Memory size59.3 KiB
2023-12-09T22:30:49.669313image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.644
Min length1

Characters and Unicode

Total characters3644
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique524 ?
Unique (%)52.4%

Sample

1st row4812
2nd row835
3rd row442
4th row1722
5th row1433
ValueCountFrequency (%)
729 10
 
1.0%
1265 9
 
0.9%
705 7
 
0.7%
1306 7
 
0.7%
1277 6
 
0.6%
702 6
 
0.6%
972 6
 
0.6%
3637 6
 
0.6%
1288 6
 
0.6%
1586 5
 
0.5%
Other values (689) 932
93.2%
2023-12-09T22:30:50.390977image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 717
19.7%
2 441
12.1%
3 381
10.5%
5 328
9.0%
7 319
8.8%
8 309
8.5%
4 306
8.4%
0 289
7.9%
9 278
 
7.6%
6 276
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3644
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 717
19.7%
2 441
12.1%
3 381
10.5%
5 328
9.0%
7 319
8.8%
8 309
8.5%
4 306
8.4%
0 289
7.9%
9 278
 
7.6%
6 276
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
Common 3644
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 717
19.7%
2 441
12.1%
3 381
10.5%
5 328
9.0%
7 319
8.8%
8 309
8.5%
4 306
8.4%
0 289
7.9%
9 278
 
7.6%
6 276
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3644
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 717
19.7%
2 441
12.1%
3 381
10.5%
5 328
9.0%
7 319
8.8%
8 309
8.5%
4 306
8.4%
0 289
7.9%
9 278
 
7.6%
6 276
 
7.6%

lot
Text

Distinct115
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T22:30:50.743304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.091
Min length1

Characters and Unicode

Total characters2091
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)2.6%

Sample

1st row1
2nd row41
3rd row28
4th row1
5th row7
ValueCountFrequency (%)
1 162
 
16.2%
7501 94
 
9.4%
29 36
 
3.6%
7502 29
 
2.9%
20 20
 
2.0%
23 18
 
1.8%
27 18
 
1.8%
22 17
 
1.7%
7 17
 
1.7%
6 16
 
1.6%
Other values (105) 573
57.3%
2023-12-09T22:30:51.227286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 471
22.5%
5 279
13.3%
2 269
12.9%
0 266
12.7%
7 240
11.5%
3 175
 
8.4%
4 118
 
5.6%
6 115
 
5.5%
9 96
 
4.6%
8 62
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2091
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 471
22.5%
5 279
13.3%
2 269
12.9%
0 266
12.7%
7 240
11.5%
3 175
 
8.4%
4 118
 
5.6%
6 115
 
5.5%
9 96
 
4.6%
8 62
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2091
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 471
22.5%
5 279
13.3%
2 269
12.9%
0 266
12.7%
7 240
11.5%
3 175
 
8.4%
4 118
 
5.6%
6 115
 
5.5%
9 96
 
4.6%
8 62
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2091
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 471
22.5%
5 279
13.3%
2 269
12.9%
0 266
12.7%
7 240
11.5%
3 175
 
8.4%
4 118
 
5.6%
6 115
 
5.5%
9 96
 
4.6%
8 62
 
3.0%

building_type
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size60.7 KiB
2023-12-09T22:30:51.386740image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5000
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOther
2nd rowOther
3rd rowOther
4th rowOther
5th rowOther
ValueCountFrequency (%)
other 1000
100.0%
2023-12-09T22:30:51.646377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 1000
20.0%
t 1000
20.0%
h 1000
20.0%
e 1000
20.0%
r 1000
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4000
80.0%
Uppercase Letter 1000
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1000
25.0%
h 1000
25.0%
e 1000
25.0%
r 1000
25.0%
Uppercase Letter
ValueCountFrequency (%)
O 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 1000
20.0%
t 1000
20.0%
h 1000
20.0%
e 1000
20.0%
r 1000
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1000
20.0%
t 1000
20.0%
h 1000
20.0%
e 1000
20.0%
r 1000
20.0%
Distinct70
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size57.2 KiB
2023-12-09T22:30:51.896760image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.493
Min length1

Characters and Unicode

Total characters1493
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.9%

Sample

1st row2
2nd row102
3rd row3
4th row3
5th row7
ValueCountFrequency (%)
7 143
 
14.3%
6 79
 
7.9%
5 56
 
5.6%
8 54
 
5.4%
4 53
 
5.3%
3 46
 
4.6%
2 46
 
4.6%
11 40
 
4.0%
12 38
 
3.8%
10 32
 
3.2%
Other values (60) 413
41.3%
2023-12-09T22:30:52.307845image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 301
20.2%
7 195
13.1%
2 195
13.1%
4 163
10.9%
3 138
9.2%
5 135
9.0%
6 134
9.0%
8 89
 
6.0%
0 77
 
5.2%
9 66
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1493
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 301
20.2%
7 195
13.1%
2 195
13.1%
4 163
10.9%
3 138
9.2%
5 135
9.0%
6 134
9.0%
8 89
 
6.0%
0 77
 
5.2%
9 66
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1493
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 301
20.2%
7 195
13.1%
2 195
13.1%
4 163
10.9%
3 138
9.2%
5 135
9.0%
6 134
9.0%
8 89
 
6.0%
0 77
 
5.2%
9 66
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 301
20.2%
7 195
13.1%
2 195
13.1%
4 163
10.9%
3 138
9.2%
5 135
9.0%
6 134
9.0%
8 89
 
6.0%
0 77
 
5.2%
9 66
 
4.4%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size60.5 KiB
2023-12-09T22:30:52.479387image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.835
Min length4

Characters and Unicode

Total characters4835
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfalse
2nd rowfalse
3rd rowfalse
4th rowfalse
5th rowfalse
ValueCountFrequency (%)
false 835
83.5%
true 165
 
16.5%
2023-12-09T22:30:52.756235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1000
20.7%
f 835
17.3%
a 835
17.3%
l 835
17.3%
s 835
17.3%
t 165
 
3.4%
r 165
 
3.4%
u 165
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4835
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1000
20.7%
f 835
17.3%
a 835
17.3%
l 835
17.3%
s 835
17.3%
t 165
 
3.4%
r 165
 
3.4%
u 165
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 4835
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1000
20.7%
f 835
17.3%
a 835
17.3%
l 835
17.3%
s 835
17.3%
t 165
 
3.4%
r 165
 
3.4%
u 165
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4835
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1000
20.7%
f 835
17.3%
a 835
17.3%
l 835
17.3%
s 835
17.3%
t 165
 
3.4%
r 165
 
3.4%
u 165
 
3.4%

associatedjobnumber
Text

MISSING 

Distinct127
Distinct (%)77.0%
Missing835
Missing (%)83.5%
Memory size36.9 KiB
2023-12-09T22:30:53.142750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters1485
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)66.1%

Sample

1st row320916407
2nd row121204035
3rd row320978064
4th row420655712
5th row321597606
ValueCountFrequency (%)
121204295 8
 
4.8%
121191414 6
 
3.6%
321592157 5
 
3.0%
121205864 4
 
2.4%
121189203 4
 
2.4%
121189828 4
 
2.4%
121191174 3
 
1.8%
421649871 2
 
1.2%
123331224 2
 
1.2%
420662982 2
 
1.2%
Other values (117) 125
75.8%
2023-12-09T22:30:53.662393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 326
22.0%
2 293
19.7%
0 146
9.8%
3 126
 
8.5%
4 116
 
7.8%
9 112
 
7.5%
5 111
 
7.5%
6 94
 
6.3%
8 80
 
5.4%
7 77
 
5.2%
Other values (3) 4
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1481
99.7%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 326
22.0%
2 293
19.8%
0 146
9.9%
3 126
 
8.5%
4 116
 
7.8%
9 112
 
7.6%
5 111
 
7.5%
6 94
 
6.3%
8 80
 
5.4%
7 77
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
M 1
25.0%
X 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1481
99.7%
Latin 4
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 326
22.0%
2 293
19.8%
0 146
9.9%
3 126
 
8.5%
4 116
 
7.8%
9 112
 
7.6%
5 111
 
7.5%
6 94
 
6.3%
8 80
 
5.4%
7 77
 
5.2%
Latin
ValueCountFrequency (%)
B 2
50.0%
M 1
25.0%
X 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 326
22.0%
2 293
19.7%
0 146
9.8%
3 126
 
8.5%
4 116
 
7.8%
9 112
 
7.5%
5 111
 
7.5%
6 94
 
6.3%
8 80
 
5.4%
7 77
 
5.2%
Other values (3) 4
 
0.3%
Distinct373
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Memory size58.7 KiB
2023-12-09T22:30:54.164003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.003
Min length1

Characters and Unicode

Total characters3003
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique249 ?
Unique (%)24.9%

Sample

1st row200
2nd row200
3rd row1
4th row40
5th row169
ValueCountFrequency (%)
200 118
 
11.8%
1 53
 
5.3%
400 43
 
4.3%
14 24
 
2.4%
10 20
 
2.0%
50 20
 
2.0%
30 17
 
1.7%
100 16
 
1.6%
225 15
 
1.5%
150 14
 
1.4%
Other values (363) 660
66.0%
2023-12-09T22:30:54.810794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 825
27.5%
1 458
15.3%
2 394
13.1%
4 284
 
9.5%
5 283
 
9.4%
3 180
 
6.0%
6 178
 
5.9%
8 161
 
5.4%
7 128
 
4.3%
9 112
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3003
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 825
27.5%
1 458
15.3%
2 394
13.1%
4 284
 
9.5%
5 283
 
9.4%
3 180
 
6.0%
6 178
 
5.9%
8 161
 
5.4%
7 128
 
4.3%
9 112
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3003
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 825
27.5%
1 458
15.3%
2 394
13.1%
4 284
 
9.5%
5 283
 
9.4%
3 180
 
6.0%
6 178
 
5.9%
8 161
 
5.4%
7 128
 
4.3%
9 112
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3003
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 825
27.5%
1 458
15.3%
2 394
13.1%
4 284
 
9.5%
5 283
 
9.4%
3 180
 
6.0%
6 178
 
5.9%
8 161
 
5.4%
7 128
 
4.3%
9 112
 
3.7%
Distinct636
Distinct (%)67.1%
Missing52
Missing (%)5.2%
Memory size75.8 KiB
2023-12-09T22:30:55.124521image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters21804
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique424 ?
Unique (%)44.7%

Sample

1st row2023-02-16T00:00:00.000
2nd row2022-02-04T00:00:00.000
3rd row2020-02-06T00:00:00.000
4th row2019-06-06T00:00:00.000
5th row2020-02-28T00:00:00.000
ValueCountFrequency (%)
2019-06-06t00:00:00.000 7
 
0.7%
2019-10-31t00:00:00.000 5
 
0.5%
2019-06-04t00:00:00.000 5
 
0.5%
2019-06-11t00:00:00.000 5
 
0.5%
2020-04-06t00:00:00.000 5
 
0.5%
2019-03-04t00:00:00.000 5
 
0.5%
2019-12-30t00:00:00.000 5
 
0.5%
2019-11-20t00:00:00.000 5
 
0.5%
2019-12-27t00:00:00.000 5
 
0.5%
2023-03-02t00:00:00.000 4
 
0.4%
Other values (626) 897
94.6%
2023-12-09T22:30:55.551157image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10837
49.7%
2 2120
 
9.7%
- 1896
 
8.7%
: 1896
 
8.7%
1 1337
 
6.1%
T 948
 
4.3%
. 948
 
4.3%
9 465
 
2.1%
3 355
 
1.6%
8 285
 
1.3%
Other values (4) 717
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16116
73.9%
Other Punctuation 2844
 
13.0%
Dash Punctuation 1896
 
8.7%
Uppercase Letter 948
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10837
67.2%
2 2120
 
13.2%
1 1337
 
8.3%
9 465
 
2.9%
3 355
 
2.2%
8 285
 
1.8%
6 202
 
1.3%
4 189
 
1.2%
7 169
 
1.0%
5 157
 
1.0%
Other Punctuation
ValueCountFrequency (%)
: 1896
66.7%
. 948
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1896
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 948
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20856
95.7%
Latin 948
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10837
52.0%
2 2120
 
10.2%
- 1896
 
9.1%
: 1896
 
9.1%
1 1337
 
6.4%
. 948
 
4.5%
9 465
 
2.2%
3 355
 
1.7%
8 285
 
1.4%
6 202
 
1.0%
Other values (3) 515
 
2.5%
Latin
ValueCountFrequency (%)
T 948
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10837
49.7%
2 2120
 
9.7%
- 1896
 
8.7%
: 1896
 
8.7%
1 1337
 
6.1%
T 948
 
4.3%
. 948
 
4.3%
9 465
 
2.1%
3 355
 
1.6%
8 285
 
1.3%
Other values (4) 717
 
3.3%

incomplete_date
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

last_incomplete_submission
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

first_objection_date
Text

MISSING 

Distinct223
Distinct (%)90.7%
Missing754
Missing (%)75.4%
Memory size42.9 KiB
2023-12-09T22:30:57.257588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters5658
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203 ?
Unique (%)82.5%

Sample

1st row2023-07-06T00:00:00.000
2nd row2022-06-02T00:00:00.000
3rd row2023-04-04T00:00:00.000
4th row2019-02-25T00:00:00.000
5th row2021-02-25T00:00:00.000
ValueCountFrequency (%)
2022-08-10t00:00:00.000 3
 
1.2%
2021-05-20t00:00:00.000 3
 
1.2%
2021-09-02t00:00:00.000 3
 
1.2%
2019-05-07t00:00:00.000 2
 
0.8%
2018-03-09t00:00:00.000 2
 
0.8%
2021-11-30t00:00:00.000 2
 
0.8%
2020-02-20t00:00:00.000 2
 
0.8%
2018-02-14t00:00:00.000 2
 
0.8%
2023-06-22t00:00:00.000 2
 
0.8%
2021-10-12t00:00:00.000 2
 
0.8%
Other values (213) 223
90.7%
2023-12-09T22:30:57.707853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2811
49.7%
2 617
 
10.9%
- 492
 
8.7%
: 492
 
8.7%
1 315
 
5.6%
T 246
 
4.3%
. 246
 
4.3%
3 104
 
1.8%
8 69
 
1.2%
9 69
 
1.2%
Other values (4) 197
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4182
73.9%
Other Punctuation 738
 
13.0%
Dash Punctuation 492
 
8.7%
Uppercase Letter 246
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2811
67.2%
2 617
 
14.8%
1 315
 
7.5%
3 104
 
2.5%
8 69
 
1.6%
9 69
 
1.6%
5 57
 
1.4%
7 51
 
1.2%
4 47
 
1.1%
6 42
 
1.0%
Other Punctuation
ValueCountFrequency (%)
: 492
66.7%
. 246
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 492
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5412
95.7%
Latin 246
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2811
51.9%
2 617
 
11.4%
- 492
 
9.1%
: 492
 
9.1%
1 315
 
5.8%
. 246
 
4.5%
3 104
 
1.9%
8 69
 
1.3%
9 69
 
1.3%
5 57
 
1.1%
Other values (3) 140
 
2.6%
Latin
ValueCountFrequency (%)
T 246
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2811
49.7%
2 617
 
10.9%
- 492
 
8.7%
: 492
 
8.7%
1 315
 
5.6%
T 246
 
4.3%
. 246
 
4.3%
3 104
 
1.8%
8 69
 
1.2%
9 69
 
1.2%
Other values (4) 197
 
3.5%

last_objection_date
Text

MISSING 

Distinct218
Distinct (%)88.6%
Missing754
Missing (%)75.4%
Memory size42.9 KiB
2023-12-09T22:30:58.005294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters5658
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)77.6%

Sample

1st row2023-07-06T00:00:00.000
2nd row2022-06-22T00:00:00.000
3rd row2023-05-03T00:00:00.000
4th row2019-02-25T00:00:00.000
5th row2021-02-25T00:00:00.000
ValueCountFrequency (%)
2022-10-25t00:00:00.000 3
 
1.2%
2022-11-10t00:00:00.000 2
 
0.8%
2019-02-07t00:00:00.000 2
 
0.8%
2021-11-30t00:00:00.000 2
 
0.8%
2023-05-03t00:00:00.000 2
 
0.8%
2020-04-03t00:00:00.000 2
 
0.8%
2021-10-14t00:00:00.000 2
 
0.8%
2023-06-22t00:00:00.000 2
 
0.8%
2018-02-23t00:00:00.000 2
 
0.8%
2023-03-20t00:00:00.000 2
 
0.8%
Other values (208) 225
91.5%
2023-12-09T22:30:58.436892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2805
49.6%
2 625
 
11.0%
- 492
 
8.7%
: 492
 
8.7%
1 314
 
5.5%
T 246
 
4.3%
. 246
 
4.3%
3 106
 
1.9%
8 69
 
1.2%
9 67
 
1.2%
Other values (4) 196
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4182
73.9%
Other Punctuation 738
 
13.0%
Dash Punctuation 492
 
8.7%
Uppercase Letter 246
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2805
67.1%
2 625
 
14.9%
1 314
 
7.5%
3 106
 
2.5%
8 69
 
1.6%
9 67
 
1.6%
5 57
 
1.4%
4 51
 
1.2%
7 50
 
1.2%
6 38
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 492
66.7%
. 246
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 492
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5412
95.7%
Latin 246
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2805
51.8%
2 625
 
11.5%
- 492
 
9.1%
: 492
 
9.1%
1 314
 
5.8%
. 246
 
4.5%
3 106
 
2.0%
8 69
 
1.3%
9 67
 
1.2%
5 57
 
1.1%
Other values (3) 139
 
2.6%
Latin
ValueCountFrequency (%)
T 246
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2805
49.6%
2 625
 
11.0%
- 492
 
8.7%
: 492
 
8.7%
1 314
 
5.5%
T 246
 
4.3%
. 246
 
4.3%
3 106
 
1.9%
8 69
 
1.2%
9 67
 
1.2%
Other values (4) 196
 
3.5%

resubmission_date
Text

MISSING 

Distinct217
Distinct (%)89.3%
Missing757
Missing (%)75.7%
Memory size42.8 KiB
2023-12-09T22:30:58.718727image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters5589
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique194 ?
Unique (%)79.8%

Sample

1st row2023-07-26T00:00:00.000
2nd row2022-06-22T00:00:00.000
3rd row2023-06-15T00:00:00.000
4th row2019-03-01T00:00:00.000
5th row2021-02-26T00:00:00.000
ValueCountFrequency (%)
2023-06-01t00:00:00.000 3
 
1.2%
2022-09-28t00:00:00.000 3
 
1.2%
2020-04-06t00:00:00.000 3
 
1.2%
2019-12-30t00:00:00.000 2
 
0.8%
2018-02-20t00:00:00.000 2
 
0.8%
2021-01-11t00:00:00.000 2
 
0.8%
2021-11-19t00:00:00.000 2
 
0.8%
2023-07-26t00:00:00.000 2
 
0.8%
2021-10-18t00:00:00.000 2
 
0.8%
2021-12-01t00:00:00.000 2
 
0.8%
Other values (207) 220
90.5%
2023-12-09T22:30:59.136096image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2775
49.7%
2 592
 
10.6%
- 486
 
8.7%
: 486
 
8.7%
1 322
 
5.8%
T 243
 
4.3%
. 243
 
4.3%
3 109
 
2.0%
9 71
 
1.3%
8 71
 
1.3%
Other values (4) 191
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4131
73.9%
Other Punctuation 729
 
13.0%
Dash Punctuation 486
 
8.7%
Uppercase Letter 243
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2775
67.2%
2 592
 
14.3%
1 322
 
7.8%
3 109
 
2.6%
9 71
 
1.7%
8 71
 
1.7%
6 54
 
1.3%
4 53
 
1.3%
7 47
 
1.1%
5 37
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 486
66.7%
. 243
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 486
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 243
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5346
95.7%
Latin 243
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2775
51.9%
2 592
 
11.1%
- 486
 
9.1%
: 486
 
9.1%
1 322
 
6.0%
. 243
 
4.5%
3 109
 
2.0%
9 71
 
1.3%
8 71
 
1.3%
6 54
 
1.0%
Other values (3) 137
 
2.6%
Latin
ValueCountFrequency (%)
T 243
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5589
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2775
49.7%
2 592
 
10.6%
- 486
 
8.7%
: 486
 
8.7%
1 322
 
5.8%
T 243
 
4.3%
. 243
 
4.3%
3 109
 
2.0%
9 71
 
1.3%
8 71
 
1.3%
Other values (4) 191
 
3.4%

permit_entire_date
Text

MISSING 

Distinct568
Distinct (%)67.5%
Missing158
Missing (%)15.8%
Memory size70.8 KiB
2023-12-09T22:30:59.502909image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters19366
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique373 ?
Unique (%)44.3%

Sample

1st row2023-02-16T00:00:00.000
2nd row2022-02-08T00:00:00.000
3rd row2023-02-08T00:00:00.000
4th row2020-02-06T00:00:00.000
5th row2019-06-06T00:00:00.000
ValueCountFrequency (%)
2020-04-07t00:00:00.000 7
 
0.8%
2019-03-04t00:00:00.000 5
 
0.6%
2019-12-27t00:00:00.000 5
 
0.6%
2019-12-23t00:00:00.000 5
 
0.6%
2019-06-06t00:00:00.000 5
 
0.6%
2019-09-06t00:00:00.000 5
 
0.6%
2023-02-14t00:00:00.000 4
 
0.5%
2019-10-31t00:00:00.000 4
 
0.5%
2023-03-02t00:00:00.000 4
 
0.5%
2019-11-14t00:00:00.000 4
 
0.5%
Other values (558) 794
94.3%
2023-12-09T22:30:59.985790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9624
49.7%
2 1878
 
9.7%
- 1684
 
8.7%
: 1684
 
8.7%
1 1206
 
6.2%
T 842
 
4.3%
. 842
 
4.3%
9 415
 
2.1%
3 301
 
1.6%
8 262
 
1.4%
Other values (4) 628
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14314
73.9%
Other Punctuation 2526
 
13.0%
Dash Punctuation 1684
 
8.7%
Uppercase Letter 842
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9624
67.2%
2 1878
 
13.1%
1 1206
 
8.4%
9 415
 
2.9%
3 301
 
2.1%
8 262
 
1.8%
6 174
 
1.2%
7 164
 
1.1%
4 155
 
1.1%
5 135
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 1684
66.7%
. 842
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1684
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 842
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18524
95.7%
Latin 842
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9624
52.0%
2 1878
 
10.1%
- 1684
 
9.1%
: 1684
 
9.1%
1 1206
 
6.5%
. 842
 
4.5%
9 415
 
2.2%
3 301
 
1.6%
8 262
 
1.4%
6 174
 
0.9%
Other values (3) 454
 
2.5%
Latin
ValueCountFrequency (%)
T 842
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9624
49.7%
2 1878
 
9.7%
- 1684
 
8.7%
: 1684
 
8.7%
1 1206
 
6.2%
T 842
 
4.3%
. 842
 
4.3%
9 415
 
2.1%
3 301
 
1.6%
8 262
 
1.4%
Other values (4) 628
 
3.2%

signedoff_date
Text

MISSING 

Distinct449
Distinct (%)65.4%
Missing313
Missing (%)31.3%
Memory size63.6 KiB
2023-12-09T22:31:00.320832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters15801
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique297 ?
Unique (%)43.2%

Sample

1st row2022-10-31T00:00:00.000
2nd row2023-06-23T00:00:00.000
3rd row2019-11-15T00:00:00.000
4th row2020-12-21T00:00:00.000
5th row2019-12-23T00:00:00.000
ValueCountFrequency (%)
2020-03-03t00:00:00.000 8
 
1.2%
2019-03-07t00:00:00.000 7
 
1.0%
2020-02-24t00:00:00.000 6
 
0.9%
2020-02-20t00:00:00.000 6
 
0.9%
2020-01-30t00:00:00.000 5
 
0.7%
2020-06-25t00:00:00.000 4
 
0.6%
2020-11-11t00:00:00.000 4
 
0.6%
2021-01-29t00:00:00.000 4
 
0.6%
2021-05-30t00:00:00.000 4
 
0.6%
2019-11-19t00:00:00.000 4
 
0.6%
Other values (439) 635
92.4%
2023-12-09T22:31:00.770869image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7964
50.4%
2 1719
 
10.9%
- 1374
 
8.7%
: 1374
 
8.7%
1 823
 
5.2%
T 687
 
4.3%
. 687
 
4.3%
3 269
 
1.7%
9 259
 
1.6%
8 148
 
0.9%
Other values (4) 497
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11679
73.9%
Other Punctuation 2061
 
13.0%
Dash Punctuation 1374
 
8.7%
Uppercase Letter 687
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7964
68.2%
2 1719
 
14.7%
1 823
 
7.0%
3 269
 
2.3%
9 259
 
2.2%
8 148
 
1.3%
7 139
 
1.2%
5 125
 
1.1%
4 120
 
1.0%
6 113
 
1.0%
Other Punctuation
ValueCountFrequency (%)
: 1374
66.7%
. 687
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1374
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 687
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15114
95.7%
Latin 687
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7964
52.7%
2 1719
 
11.4%
- 1374
 
9.1%
: 1374
 
9.1%
1 823
 
5.4%
. 687
 
4.5%
3 269
 
1.8%
9 259
 
1.7%
8 148
 
1.0%
7 139
 
0.9%
Other values (3) 358
 
2.4%
Latin
ValueCountFrequency (%)
T 687
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15801
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7964
50.4%
2 1719
 
10.9%
- 1374
 
8.7%
: 1374
 
8.7%
1 823
 
5.2%
T 687
 
4.3%
. 687
 
4.3%
3 269
 
1.7%
9 259
 
1.6%
8 148
 
0.9%
Other values (4) 497
 
3.1%
Distinct50
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size62.1 KiB
2023-12-09T22:31:01.061741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length7
Mean length6.47
Min length3

Characters and Unicode

Total characters6470
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)1.8%

Sample

1st rowKIRK
2nd rowGERALD
3rd rowGREGORY
4th rowADAM
5th rowDAVID
ValueCountFrequency (%)
william 237
21.8%
shaheed 106
9.8%
david 85
 
7.8%
richard 82
 
7.6%
gerald 65
 
6.0%
md 60
 
5.5%
tohfaz 60
 
5.5%
boris 58
 
5.3%
gregory 51
 
4.7%
adam 27
 
2.5%
Other values (42) 254
23.4%
2023-12-09T22:31:01.522657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 805
12.4%
I 747
11.5%
L 592
9.1%
D 548
 
8.5%
R 530
 
8.2%
E 496
 
7.7%
H 439
 
6.8%
M 355
 
5.5%
O 286
 
4.4%
W 250
 
3.9%
Other values (17) 1422
22.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6383
98.7%
Space Separator 85
 
1.3%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 805
12.6%
I 747
11.7%
L 592
9.3%
D 548
8.6%
R 530
 
8.3%
E 496
 
7.8%
H 439
 
6.9%
M 355
 
5.6%
O 286
 
4.5%
W 250
 
3.9%
Other values (14) 1335
20.9%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6383
98.7%
Common 87
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 805
12.6%
I 747
11.7%
L 592
9.3%
D 548
8.6%
R 530
 
8.3%
E 496
 
7.8%
H 439
 
6.9%
M 355
 
5.6%
O 286
 
4.5%
W 250
 
3.9%
Other values (14) 1335
20.9%
Common
ValueCountFrequency (%)
85
97.7%
. 1
 
1.1%
, 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 805
12.4%
I 747
11.5%
L 592
9.1%
D 548
 
8.5%
R 530
 
8.2%
E 496
 
7.7%
H 439
 
6.8%
M 355
 
5.5%
O 286
 
4.4%
W 250
 
3.9%
Other values (17) 1422
22.0%
Distinct71
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size62.5 KiB
2023-12-09T22:31:01.830364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.873
Min length2

Characters and Unicode

Total characters6873
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)3.5%

Sample

1st rowMAYER
2nd rowFRASCELLI
3rd rowALBERTSON
4th rowBEZNICKI
5th rowKRAUSMAN
ValueCountFrequency (%)
mensche 232
23.1%
baksh 106
10.6%
krausman 85
 
8.5%
frascelli 81
 
8.1%
licht 80
 
8.0%
uddin 60
 
6.0%
evelkin 58
 
5.8%
albertson 51
 
5.1%
beznicki 27
 
2.7%
bockhaus 25
 
2.5%
Other values (63) 198
19.7%
2023-12-09T22:31:02.279606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 863
12.6%
S 649
 
9.4%
N 603
 
8.8%
A 563
 
8.2%
C 503
 
7.3%
H 485
 
7.1%
L 429
 
6.2%
I 412
 
6.0%
M 376
 
5.5%
K 331
 
4.8%
Other values (19) 1659
24.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6861
99.8%
Other Punctuation 7
 
0.1%
Space Separator 5
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 863
12.6%
S 649
 
9.5%
N 603
 
8.8%
A 563
 
8.2%
C 503
 
7.3%
H 485
 
7.1%
L 429
 
6.3%
I 412
 
6.0%
M 376
 
5.5%
K 331
 
4.8%
Other values (15) 1647
24.0%
Other Punctuation
ValueCountFrequency (%)
. 4
57.1%
' 2
28.6%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6861
99.8%
Common 12
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 863
12.6%
S 649
 
9.5%
N 603
 
8.8%
A 563
 
8.2%
C 503
 
7.3%
H 485
 
7.1%
L 429
 
6.3%
I 412
 
6.0%
M 376
 
5.5%
K 331
 
4.8%
Other values (15) 1647
24.0%
Common
ValueCountFrequency (%)
5
41.7%
. 4
33.3%
' 2
 
16.7%
, 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 863
12.6%
S 649
 
9.4%
N 603
 
8.8%
A 563
 
8.2%
C 503
 
7.3%
H 485
 
7.1%
L 429
 
6.2%
I 412
 
6.0%
M 376
 
5.5%
K 331
 
4.8%
Other values (19) 1659
24.1%
Distinct68
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size77.8 KiB
2023-12-09T22:31:02.573363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length33
Mean length22.541
Min length9

Characters and Unicode

Total characters22541
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)3.4%

Sample

1st rowBart Elevator Services. Inc.
2nd rowOTIS ELEVATOR COMPANY
3rd rowPRECISION ELEVATOR CORP
4th rowTK ELEVATOR CORPORATION
5th rowBERGEN-PASSAIC ELEV OF NY
ValueCountFrequency (%)
elevator 552
 
14.5%
corp 307
 
8.1%
elev 275
 
7.2%
schindler 232
 
6.1%
163
 
4.3%
lift 140
 
3.7%
co 117
 
3.1%
inc 107
 
2.8%
mobility 106
 
2.8%
i 106
 
2.8%
Other values (120) 1698
44.6%
2023-12-09T22:31:03.006490image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2803
12.4%
E 2607
11.6%
L 1786
 
7.9%
I 1620
 
7.2%
O 1612
 
7.2%
R 1575
 
7.0%
C 1411
 
6.3%
T 1224
 
5.4%
N 1146
 
5.1%
A 1126
 
5.0%
Other values (32) 5631
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 19134
84.9%
Space Separator 2803
 
12.4%
Other Punctuation 499
 
2.2%
Dash Punctuation 86
 
0.4%
Lowercase Letter 19
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 2607
13.6%
L 1786
9.3%
I 1620
 
8.5%
O 1612
 
8.4%
R 1575
 
8.2%
C 1411
 
7.4%
T 1224
 
6.4%
N 1146
 
6.0%
A 1126
 
5.9%
V 882
 
4.6%
Other values (16) 4145
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 3
15.8%
r 3
15.8%
c 2
10.5%
v 2
10.5%
t 2
10.5%
a 2
10.5%
o 1
 
5.3%
i 1
 
5.3%
s 1
 
5.3%
n 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 297
59.5%
& 168
33.7%
, 34
 
6.8%
Space Separator
ValueCountFrequency (%)
2803
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19153
85.0%
Common 3388
 
15.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 2607
13.6%
L 1786
9.3%
I 1620
 
8.5%
O 1612
 
8.4%
R 1575
 
8.2%
C 1411
 
7.4%
T 1224
 
6.4%
N 1146
 
6.0%
A 1126
 
5.9%
V 882
 
4.6%
Other values (27) 4164
21.7%
Common
ValueCountFrequency (%)
2803
82.7%
. 297
 
8.8%
& 168
 
5.0%
- 86
 
2.5%
, 34
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2803
12.4%
E 2607
11.6%
L 1786
 
7.9%
I 1620
 
7.2%
O 1612
 
7.2%
R 1575
 
7.0%
C 1411
 
6.3%
T 1224
 
5.4%
N 1146
 
5.1%
A 1126
 
5.0%
Other values (32) 5631
25.0%

applicant_address
Text

MISSING 

Distinct48
Distinct (%)19.6%
Missing755
Missing (%)75.5%
Memory size42.2 KiB
2023-12-09T22:31:03.300899image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length43
Median length35
Mean length20.34693878
Min length3

Characters and Unicode

Total characters4985
Distinct characters50
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)7.8%

Sample

1st row247 West 30th St., 6th Floor
2nd row519 8TH AVENUE
3rd row1 PENN PLAZA,250 W 34ST
4th row61-43 186TH STREET
5th row53-01 11TH STREET
ValueCountFrequency (%)
street 64
 
6.9%
59-40 60
 
6.5%
blvd 60
 
6.5%
queens 60
 
6.5%
avenue 52
 
5.6%
floor 40
 
4.3%
east 31
 
3.4%
49th 25
 
2.7%
w 20
 
2.2%
750 18
 
1.9%
Other values (100) 494
53.5%
2023-12-09T22:31:03.749424image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
679
 
13.6%
E 417
 
8.4%
T 260
 
5.2%
A 207
 
4.2%
S 204
 
4.1%
N 199
 
4.0%
1 196
 
3.9%
O 169
 
3.4%
R 162
 
3.2%
L 160
 
3.2%
Other values (40) 2332
46.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2771
55.6%
Decimal Number 1080
 
21.7%
Space Separator 679
 
13.6%
Lowercase Letter 213
 
4.3%
Other Punctuation 163
 
3.3%
Dash Punctuation 79
 
1.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 417
15.0%
T 260
 
9.4%
A 207
 
7.5%
S 204
 
7.4%
N 199
 
7.2%
O 169
 
6.1%
R 162
 
5.8%
L 160
 
5.8%
U 138
 
5.0%
V 128
 
4.6%
Other values (15) 727
26.2%
Decimal Number
ValueCountFrequency (%)
1 196
18.1%
0 157
14.5%
4 137
12.7%
9 133
12.3%
5 133
12.3%
2 95
8.8%
3 74
 
6.9%
8 55
 
5.1%
6 50
 
4.6%
7 50
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
t 81
38.0%
e 45
21.1%
r 26
 
12.2%
s 20
 
9.4%
h 18
 
8.5%
a 18
 
8.5%
k 2
 
0.9%
o 2
 
0.9%
l 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 85
52.1%
. 64
39.3%
/ 7
 
4.3%
# 7
 
4.3%
Space Separator
ValueCountFrequency (%)
679
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2984
59.9%
Common 2001
40.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 417
14.0%
T 260
 
8.7%
A 207
 
6.9%
S 204
 
6.8%
N 199
 
6.7%
O 169
 
5.7%
R 162
 
5.4%
L 160
 
5.4%
U 138
 
4.6%
V 128
 
4.3%
Other values (24) 940
31.5%
Common
ValueCountFrequency (%)
679
33.9%
1 196
 
9.8%
0 157
 
7.8%
4 137
 
6.8%
9 133
 
6.6%
5 133
 
6.6%
2 95
 
4.7%
, 85
 
4.2%
- 79
 
3.9%
3 74
 
3.7%
Other values (6) 233
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4985
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
679
 
13.6%
E 417
 
8.4%
T 260
 
5.2%
A 207
 
4.2%
S 204
 
4.1%
N 199
 
4.0%
1 196
 
3.9%
O 169
 
3.4%
R 162
 
3.2%
L 160
 
3.2%
Other values (40) 2332
46.8%
Distinct24
Distinct (%)2.4%
Missing8
Missing (%)0.8%
Memory size63.5 KiB
2023-12-09T22:31:03.973608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length17
Median length8
Mean length8.109879032
Min length5

Characters and Unicode

Total characters8045
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.0%

Sample

1st rowNew York
2nd rowNEW YORK
3rd rowBROOKLYN
4th rowNEW YORK
5th rowBRONX
ValueCountFrequency (%)
new 523
31.4%
york 523
31.4%
brooklyn 145
 
8.7%
bronx 113
 
6.8%
ozone 76
 
4.6%
park 76
 
4.6%
woodside 60
 
3.6%
island 44
 
2.6%
long 26
 
1.6%
staten 18
 
1.1%
Other values (17) 59
 
3.5%
2023-12-09T22:31:04.356924image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 1241
15.4%
N 953
11.8%
R 877
10.9%
K 743
9.2%
E 705
8.8%
Y 686
8.5%
671
8.3%
W 592
7.4%
B 258
 
3.2%
L 234
 
2.9%
Other values (21) 1085
13.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7366
91.6%
Space Separator 671
 
8.3%
Lowercase Letter 5
 
0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 1241
16.8%
N 953
12.9%
R 877
11.9%
K 743
10.1%
E 705
9.6%
Y 686
9.3%
W 592
8.0%
B 258
 
3.5%
L 234
 
3.2%
D 183
 
2.5%
Other values (14) 894
12.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
w 1
20.0%
o 1
20.0%
r 1
20.0%
k 1
20.0%
Space Separator
ValueCountFrequency (%)
671
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7371
91.6%
Common 674
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 1241
16.8%
N 953
12.9%
R 877
11.9%
K 743
10.1%
E 705
9.6%
Y 686
9.3%
W 592
8.0%
B 258
 
3.5%
L 234
 
3.2%
D 183
 
2.5%
Other values (19) 899
12.2%
Common
ValueCountFrequency (%)
671
99.6%
, 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8045
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1241
15.4%
N 953
11.8%
R 877
10.9%
K 743
9.2%
E 705
8.8%
Y 686
8.5%
671
8.3%
W 592
7.4%
B 258
 
3.2%
L 234
 
2.9%
Other values (21) 1085
13.5%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T22:31:04.481153image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNY
2nd rowNY
3rd rowNY
4th rowNY
5th rowNY
ValueCountFrequency (%)
ny 984
98.4%
nj 16
 
1.6%
2023-12-09T22:31:04.726621image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
Y 984
49.2%
J 16
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2000
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
50.0%
Y 984
49.2%
J 16
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
Y 984
49.2%
J 16
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
Y 984
49.2%
J 16
 
0.8%
Distinct45
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size60.7 KiB
2023-12-09T22:31:04.963011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.005
Min length5

Characters and Unicode

Total characters5005
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)1.7%

Sample

1st row10001
2nd row10119
3rd row11220
4th row10018
5th row10462
ValueCountFrequency (%)
10017 193
19.3%
10036 146
14.6%
10462 85
8.5%
10119 83
8.3%
11416 77
 
7.7%
11377 60
 
6.0%
11235 58
 
5.8%
11220 56
 
5.6%
10018 29
 
2.9%
11101 25
 
2.5%
Other values (35) 188
18.8%
2023-12-09T22:31:05.328577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1903
38.0%
0 1277
25.5%
2 352
 
7.0%
7 349
 
7.0%
6 348
 
7.0%
3 324
 
6.5%
4 227
 
4.5%
9 88
 
1.8%
5 72
 
1.4%
8 64
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5004
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1903
38.0%
0 1277
25.5%
2 352
 
7.0%
7 349
 
7.0%
6 348
 
7.0%
3 324
 
6.5%
4 227
 
4.5%
9 88
 
1.8%
5 72
 
1.4%
8 64
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5005
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1903
38.0%
0 1277
25.5%
2 352
 
7.0%
7 349
 
7.0%
6 348
 
7.0%
3 324
 
6.5%
4 227
 
4.5%
9 88
 
1.8%
5 72
 
1.4%
8 64
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1903
38.0%
0 1277
25.5%
2 352
 
7.0%
7 349
 
7.0%
6 348
 
7.0%
3 324
 
6.5%
4 227
 
4.5%
9 88
 
1.8%
5 72
 
1.4%
8 64
 
1.3%
Distinct72
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
2023-12-09T22:31:05.537233image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.088
Min length10

Characters and Unicode

Total characters10088
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)3.7%

Sample

1st rowL - 038064
2nd rowL - 056001
3rd rowL - 610047
4th rowL - 610055
5th rowL - 610072
ValueCountFrequency (%)
1000
33.3%
l 912
30.4%
074117 232
 
7.7%
601001 106
 
3.5%
610072 85
 
2.8%
pe 85
 
2.8%
056001 81
 
2.7%
523001 80
 
2.7%
556001 65
 
2.2%
071719 60
 
2.0%
Other values (66) 294
 
9.8%
2023-12-09T22:31:05.866528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2000
19.8%
0 1845
18.3%
1 1454
14.4%
- 1000
9.9%
L 912
9.0%
7 805
8.0%
6 550
 
5.5%
5 453
 
4.5%
4 330
 
3.3%
2 243
 
2.4%
Other values (7) 496
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6000
59.5%
Space Separator 2000
 
19.8%
Uppercase Letter 1088
 
10.8%
Dash Punctuation 1000
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1845
30.8%
1 1454
24.2%
7 805
13.4%
6 550
 
9.2%
5 453
 
7.5%
4 330
 
5.5%
2 243
 
4.0%
3 174
 
2.9%
9 102
 
1.7%
8 44
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
L 912
83.8%
P 85
 
7.8%
E 85
 
7.8%
R 3
 
0.3%
A 3
 
0.3%
Space Separator
ValueCountFrequency (%)
2000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9000
89.2%
Latin 1088
 
10.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2000
22.2%
0 1845
20.5%
1 1454
16.2%
- 1000
11.1%
7 805
8.9%
6 550
 
6.1%
5 453
 
5.0%
4 330
 
3.7%
2 243
 
2.7%
3 174
 
1.9%
Other values (2) 146
 
1.6%
Latin
ValueCountFrequency (%)
L 912
83.8%
P 85
 
7.8%
E 85
 
7.8%
R 3
 
0.3%
A 3
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2000
19.8%
0 1845
18.3%
1 1454
14.4%
- 1000
9.9%
L 912
9.0%
7 805
8.0%
6 550
 
5.5%
5 453
 
4.5%
4 330
 
3.3%
2 243
 
2.4%
Other values (7) 496
 
4.9%
Distinct17
Distinct (%)2.6%
Missing345
Missing (%)34.5%
Memory size50.8 KiB
2023-12-09T22:31:06.074719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.334351145
Min length4

Characters and Unicode

Total characters3494
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowFRED
2nd rowKOKO
3rd rowMILES
4th rowWILLIAM
5th rowMILES
ValueCountFrequency (%)
miles 127
19.1%
jerry 106
15.9%
koko 85
12.8%
fred 60
9.0%
chang 54
8.1%
william 54
8.1%
wayne 50
 
7.5%
alessandro 36
 
5.4%
robert 25
 
3.8%
inhwan 23
 
3.5%
Other values (7) 46
 
6.9%
2023-12-09T22:31:06.407286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 420
12.0%
R 364
10.4%
L 277
 
7.9%
A 268
 
7.7%
I 264
 
7.6%
O 253
 
7.2%
N 212
 
6.1%
S 199
 
5.7%
M 198
 
5.7%
K 170
 
4.9%
Other values (11) 869
24.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3483
99.7%
Space Separator 11
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 420
12.1%
R 364
10.5%
L 277
 
8.0%
A 268
 
7.7%
I 264
 
7.6%
O 253
 
7.3%
N 212
 
6.1%
S 199
 
5.7%
M 198
 
5.7%
K 170
 
4.9%
Other values (10) 858
24.6%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3483
99.7%
Common 11
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 420
12.1%
R 364
10.5%
L 277
 
8.0%
A 268
 
7.7%
I 264
 
7.6%
O 253
 
7.3%
N 212
 
6.1%
S 199
 
5.7%
M 198
 
5.7%
K 170
 
4.9%
Other values (10) 858
24.6%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 420
12.0%
R 364
10.4%
L 277
 
7.9%
A 268
 
7.7%
I 264
 
7.6%
O 253
 
7.2%
N 212
 
6.1%
S 199
 
5.7%
M 198
 
5.7%
K 170
 
4.9%
Other values (11) 869
24.9%
Distinct16
Distinct (%)2.4%
Missing345
Missing (%)34.5%
Memory size51.0 KiB
2023-12-09T22:31:06.606212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.72519084
Min length3

Characters and Unicode

Total characters3750
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowTORRICO
2nd rowUYO
3rd rowLAMB
4th rowMADDEN
5th rowLAMB
ValueCountFrequency (%)
lamb 127
16.3%
bruno 106
13.6%
jr 106
13.6%
uyo 85
10.9%
torrico 60
7.7%
madden 54
6.9%
park 54
6.9%
clarke 50
 
6.4%
cercone 36
 
4.6%
murphy 25
 
3.2%
Other values (8) 74
9.5%
2023-12-09T22:31:06.942053image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 497
13.3%
O 354
 
9.4%
A 352
 
9.4%
B 233
 
6.2%
U 232
 
6.2%
N 223
 
5.9%
C 221
 
5.9%
M 215
 
5.7%
L 207
 
5.5%
E 182
 
4.9%
Other values (14) 1034
27.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3522
93.9%
Space Separator 122
 
3.3%
Other Punctuation 106
 
2.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 497
14.1%
O 354
10.1%
A 352
10.0%
B 233
 
6.6%
U 232
 
6.6%
N 223
 
6.3%
C 221
 
6.3%
M 215
 
6.1%
L 207
 
5.9%
E 182
 
5.2%
Other values (12) 806
22.9%
Space Separator
ValueCountFrequency (%)
122
100.0%
Other Punctuation
ValueCountFrequency (%)
. 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3522
93.9%
Common 228
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 497
14.1%
O 354
10.1%
A 352
10.0%
B 233
 
6.6%
U 232
 
6.6%
N 223
 
6.3%
C 221
 
6.3%
M 215
 
6.1%
L 207
 
5.9%
E 182
 
5.2%
Other values (12) 806
22.9%
Common
ValueCountFrequency (%)
122
53.5%
. 106
46.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 497
13.3%
O 354
 
9.4%
A 352
 
9.4%
B 233
 
6.2%
U 232
 
6.2%
N 223
 
5.9%
C 221
 
5.9%
M 215
 
5.7%
L 207
 
5.5%
E 182
 
4.9%
Other values (14) 1034
27.6%

designprofessional
Text

MISSING 

Distinct19
Distinct (%)2.9%
Missing345
Missing (%)34.5%
Memory size62.1 KiB
2023-12-09T22:31:07.208503image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length35
Median length29
Mean length23.10076336
Min length2

Characters and Unicode

Total characters15131
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st rowFRED W. TORRICO ARCHITECT
2nd rowRICK KRAMER ARCHITECT, P.C.
3rd rowSCHINDLER ELEVATOR
4th rowWILLIAM MADDEN ENGINEER CONSTRUCTIO
5th rowSCHINDLER ELEVATOR
ValueCountFrequency (%)
architect 202
 
9.0%
p.c 138
 
6.2%
schindler 127
 
5.7%
elevator 127
 
5.7%
anthony 108
 
4.8%
jerry 106
 
4.7%
bruno 106
 
4.7%
jr 106
 
4.7%
aia 106
 
4.7%
solutions 86
 
3.9%
Other values (43) 1021
45.7%
2023-12-09T22:31:07.618672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1605
 
10.6%
1578
 
10.4%
E 1240
 
8.2%
C 1131
 
7.5%
A 1071
 
7.1%
I 1021
 
6.7%
T 951
 
6.3%
N 916
 
6.1%
O 783
 
5.2%
L 519
 
3.4%
Other values (18) 4316
28.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 12828
84.8%
Space Separator 1578
 
10.4%
Other Punctuation 724
 
4.8%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 1605
12.5%
E 1240
9.7%
C 1131
 
8.8%
A 1071
 
8.3%
I 1021
 
8.0%
T 951
 
7.4%
N 916
 
7.1%
O 783
 
6.1%
L 519
 
4.0%
H 501
 
3.9%
Other values (14) 3090
24.1%
Other Punctuation
ValueCountFrequency (%)
. 462
63.8%
, 262
36.2%
Space Separator
ValueCountFrequency (%)
1578
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12828
84.8%
Common 2303
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 1605
12.5%
E 1240
9.7%
C 1131
 
8.8%
A 1071
 
8.3%
I 1021
 
8.0%
T 951
 
7.4%
N 916
 
7.1%
O 783
 
6.1%
L 519
 
4.0%
H 501
 
3.9%
Other values (14) 3090
24.1%
Common
ValueCountFrequency (%)
1578
68.5%
. 462
 
20.1%
, 262
 
11.4%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15131
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 1605
 
10.6%
1578
 
10.4%
E 1240
 
8.2%
C 1131
 
7.5%
A 1071
 
7.1%
I 1021
 
6.7%
T 951
 
6.3%
N 916
 
6.1%
O 783
 
5.2%
L 519
 
3.4%
Other values (18) 4316
28.5%
Distinct21
Distinct (%)3.2%
Missing344
Missing (%)34.4%
Memory size58.6 KiB
2023-12-09T22:31:07.891649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.51676829
Min length7

Characters and Unicode

Total characters11491
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row33-16 104TH STREET
2nd row36 OSCEOLA AVENUE
3rd row20 WHIPPANY ROAD
4th row96 LINWOOD PLAZA, #2
5th row20 WHIPPANY ROAD
ValueCountFrequency (%)
street 235
 
11.0%
avenue 134
 
6.3%
whippany 127
 
5.9%
20 127
 
5.9%
road 127
 
5.9%
farrington 106
 
4.9%
9 106
 
4.9%
36 80
 
3.7%
osceola 80
 
3.7%
2 63
 
2.9%
Other values (52) 957
44.7%
2023-12-09T22:31:08.310257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1491
 
13.0%
E 997
 
8.7%
A 851
 
7.4%
R 732
 
6.4%
T 712
 
6.2%
N 568
 
4.9%
O 487
 
4.2%
1 373
 
3.2%
2 358
 
3.1%
3 357
 
3.1%
Other values (29) 4565
39.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7388
64.3%
Decimal Number 2254
 
19.6%
Space Separator 1491
 
13.0%
Dash Punctuation 188
 
1.6%
Other Punctuation 170
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 997
13.5%
A 851
11.5%
R 732
9.9%
T 712
9.6%
N 568
 
7.7%
O 487
 
6.6%
I 354
 
4.8%
S 347
 
4.7%
P 337
 
4.6%
L 283
 
3.8%
Other values (13) 1720
23.3%
Decimal Number
ValueCountFrequency (%)
1 373
16.5%
2 358
15.9%
3 357
15.8%
6 315
14.0%
0 252
11.2%
9 209
9.3%
4 203
9.0%
7 80
 
3.5%
8 66
 
2.9%
5 41
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 81
47.6%
# 63
37.1%
. 20
 
11.8%
' 6
 
3.5%
Space Separator
ValueCountFrequency (%)
1491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7388
64.3%
Common 4103
35.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 997
13.5%
A 851
11.5%
R 732
9.9%
T 712
9.6%
N 568
 
7.7%
O 487
 
6.6%
I 354
 
4.8%
S 347
 
4.7%
P 337
 
4.6%
L 283
 
3.8%
Other values (13) 1720
23.3%
Common
ValueCountFrequency (%)
1491
36.3%
1 373
 
9.1%
2 358
 
8.7%
3 357
 
8.7%
6 315
 
7.7%
0 252
 
6.1%
9 209
 
5.1%
4 203
 
4.9%
- 188
 
4.6%
, 81
 
2.0%
Other values (6) 276
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11491
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1491
 
13.0%
E 997
 
8.7%
A 851
 
7.4%
R 732
 
6.4%
T 712
 
6.2%
N 568
 
4.9%
O 487
 
4.2%
1 373
 
3.2%
2 358
 
3.1%
3 357
 
3.1%
Other values (29) 4565
39.7%
Distinct18
Distinct (%)2.7%
Missing344
Missing (%)34.4%
Memory size54.1 KiB
2023-12-09T22:31:08.541498image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length12
Mean length10.46493902
Min length5

Characters and Unicode

Total characters6865
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowCORONA
2nd rowDOBBS FERRY
3rd rowMORRISTOWN
4th rowFORT LEE
5th rowMORRISTOWN
ValueCountFrequency (%)
west 131
12.0%
morristown 127
11.6%
caldwell 106
 
9.7%
dobbs 80
 
7.3%
ferry 80
 
7.3%
city 61
 
5.6%
corona 60
 
5.5%
long 54
 
4.9%
island 54
 
4.9%
jamaica 50
 
4.6%
Other values (15) 292
26.7%
2023-12-09T22:31:08.894253image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 690
 
10.1%
R 622
 
9.1%
L 580
 
8.4%
E 473
 
6.9%
A 444
 
6.5%
W 440
 
6.4%
439
 
6.4%
S 418
 
6.1%
N 410
 
6.0%
T 365
 
5.3%
Other values (20) 1984
28.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6419
93.5%
Space Separator 439
 
6.4%
Lowercase Letter 7
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 690
10.7%
R 622
 
9.7%
L 580
 
9.0%
E 473
 
7.4%
A 444
 
6.9%
W 440
 
6.9%
S 418
 
6.5%
N 410
 
6.4%
T 365
 
5.7%
I 343
 
5.3%
Other values (13) 1634
25.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
r 1
14.3%
a 1
14.3%
t 1
14.3%
c 1
14.3%
k 1
14.3%
Space Separator
ValueCountFrequency (%)
439
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6426
93.6%
Common 439
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 690
10.7%
R 622
 
9.7%
L 580
 
9.0%
E 473
 
7.4%
A 444
 
6.9%
W 440
 
6.8%
S 418
 
6.5%
N 410
 
6.4%
T 365
 
5.7%
I 343
 
5.3%
Other values (19) 1641
25.5%
Common
ValueCountFrequency (%)
439
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6865
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 690
 
10.1%
R 622
 
9.1%
L 580
 
8.4%
E 473
 
6.9%
A 444
 
6.5%
W 440
 
6.4%
439
 
6.4%
S 418
 
6.1%
N 410
 
6.0%
T 365
 
5.3%
Other values (20) 1984
28.9%
Distinct2
Distinct (%)0.3%
Missing344
Missing (%)34.4%
Memory size48.7 KiB
2023-12-09T22:31:09.059191image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1312
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNY
2nd rowNY
3rd rowNJ
4th rowNJ
5th rowNJ
ValueCountFrequency (%)
nj 337
51.4%
ny 319
48.6%
2023-12-09T22:31:09.352528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 656
50.0%
J 337
25.7%
Y 319
24.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1312
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 656
50.0%
J 337
25.7%
Y 319
24.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 1312
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 656
50.0%
J 337
25.7%
Y 319
24.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 656
50.0%
J 337
25.7%
Y 319
24.3%
Distinct21
Distinct (%)3.2%
Missing344
Missing (%)34.4%
Memory size50.6 KiB
2023-12-09T22:31:09.548288image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters3280
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row11368
2nd row10522
3rd row07960
4th row07024
5th row07960
ValueCountFrequency (%)
07960 127
19.4%
07006 106
16.2%
10522 80
12.2%
11368 60
9.1%
11101 54
8.2%
11435 50
 
7.6%
07024 40
 
6.1%
07424 36
 
5.5%
07480 25
 
3.8%
11358 23
 
3.5%
Other values (11) 55
8.4%
2023-12-09T22:31:09.869010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 973
29.7%
1 647
19.7%
7 340
 
10.4%
6 303
 
9.2%
2 247
 
7.5%
4 196
 
6.0%
5 159
 
4.8%
3 145
 
4.4%
9 137
 
4.2%
8 133
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3280
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 973
29.7%
1 647
19.7%
7 340
 
10.4%
6 303
 
9.2%
2 247
 
7.5%
4 196
 
6.0%
5 159
 
4.8%
3 145
 
4.4%
9 137
 
4.2%
8 133
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3280
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 973
29.7%
1 647
19.7%
7 340
 
10.4%
6 303
 
9.2%
2 247
 
7.5%
4 196
 
6.0%
5 159
 
4.8%
3 145
 
4.4%
9 137
 
4.2%
8 133
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 973
29.7%
1 647
19.7%
7 340
 
10.4%
6 303
 
9.2%
2 247
 
7.5%
4 196
 
6.0%
5 159
 
4.8%
3 145
 
4.4%
9 137
 
4.2%
8 133
 
4.1%
Distinct18
Distinct (%)2.7%
Missing344
Missing (%)34.4%
Memory size54.4 KiB
2023-12-09T22:31:10.044462image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.99542683
Min length10

Characters and Unicode

Total characters7213
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowRA - 023257
2nd rowRA - 028990
3rd rowPE - 082175
4th rowPE - 063923
5th rowPE - 082175
ValueCountFrequency (%)
656
33.3%
ra 335
17.0%
pe 318
16.2%
082175 127
 
6.5%
032187 106
 
5.4%
028990 85
 
4.3%
023257 60
 
3.0%
063923 54
 
2.7%
024582 53
 
2.7%
065950 50
 
2.5%
Other values (12) 124
 
6.3%
2023-12-09T22:31:10.344659image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1312
18.2%
0 824
11.4%
- 656
9.1%
2 632
8.8%
8 424
 
5.9%
3 400
 
5.5%
9 392
 
5.4%
5 362
 
5.0%
R 335
 
4.6%
A 335
 
4.6%
Other values (7) 1541
21.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3936
54.6%
Space Separator 1312
 
18.2%
Uppercase Letter 1309
 
18.1%
Dash Punctuation 656
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 824
20.9%
2 632
16.1%
8 424
10.8%
3 400
10.2%
9 392
10.0%
5 362
9.2%
1 334
8.5%
7 327
 
8.3%
6 129
 
3.3%
4 112
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
R 335
25.6%
A 335
25.6%
P 318
24.3%
E 318
24.3%
L 3
 
0.2%
Space Separator
ValueCountFrequency (%)
1312
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5904
81.9%
Latin 1309
 
18.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1312
22.2%
0 824
14.0%
- 656
11.1%
2 632
10.7%
8 424
 
7.2%
3 400
 
6.8%
9 392
 
6.6%
5 362
 
6.1%
1 334
 
5.7%
7 327
 
5.5%
Other values (2) 241
 
4.1%
Latin
ValueCountFrequency (%)
R 335
25.6%
A 335
25.6%
P 318
24.3%
E 318
24.3%
L 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7213
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1312
18.2%
0 824
11.4%
- 656
9.1%
2 632
8.8%
8 424
 
5.9%
3 400
 
5.5%
9 392
 
5.4%
5 362
 
5.0%
R 335
 
4.6%
A 335
 
4.6%
Other values (7) 1541
21.4%
Distinct422
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Memory size61.4 KiB
2023-12-09T22:31:10.737452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length14
Mean length5.749
Min length1

Characters and Unicode

Total characters5749
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique265 ?
Unique (%)26.5%

Sample

1st rowJOHN
2nd rowDIANE
3rd rowGEORGE
4th rowROPO
5th rowDEBORAH
ValueCountFrequency (%)
michael 33
 
3.2%
david 33
 
3.2%
robert 19
 
1.9%
brian 18
 
1.8%
william 18
 
1.8%
james 18
 
1.8%
joseph 17
 
1.7%
john 17
 
1.7%
diana 16
 
1.6%
allie 15
 
1.5%
Other values (423) 814
80.0%
2023-12-09T22:31:11.296894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 722
12.6%
E 651
11.3%
I 510
 
8.9%
N 481
 
8.4%
R 440
 
7.7%
L 341
 
5.9%
S 264
 
4.6%
H 255
 
4.4%
D 253
 
4.4%
O 247
 
4.3%
Other values (23) 1585
27.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 5722
99.5%
Space Separator 18
 
0.3%
Decimal Number 7
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 722
12.6%
E 651
11.4%
I 510
 
8.9%
N 481
 
8.4%
R 440
 
7.7%
L 341
 
6.0%
S 264
 
4.6%
H 255
 
4.5%
D 253
 
4.4%
O 247
 
4.3%
Other values (16) 1558
27.2%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
1 2
28.6%
0 1
14.3%
7 1
14.3%
3 1
14.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5722
99.5%
Common 27
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 722
12.6%
E 651
11.4%
I 510
 
8.9%
N 481
 
8.4%
R 440
 
7.7%
L 341
 
6.0%
S 264
 
4.6%
H 255
 
4.5%
D 253
 
4.4%
O 247
 
4.3%
Other values (16) 1558
27.2%
Common
ValueCountFrequency (%)
18
66.7%
2 2
 
7.4%
1 2
 
7.4%
. 2
 
7.4%
0 1
 
3.7%
7 1
 
3.7%
3 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5749
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 722
12.6%
E 651
11.3%
I 510
 
8.9%
N 481
 
8.4%
R 440
 
7.7%
L 341
 
5.9%
S 264
 
4.6%
H 255
 
4.4%
D 253
 
4.4%
O 247
 
4.3%
Other values (23) 1585
27.6%
Distinct643
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size62.2 KiB
2023-12-09T22:31:11.703419image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length13
Mean length6.611
Min length2

Characters and Unicode

Total characters6611
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique477 ?
Unique (%)47.7%

Sample

1st rowEVES
2nd rowFIELDS
3rd rowKOUTSOS
4th rowOYEBODE
5th rowMINERVINI
ValueCountFrequency (%)
freiman 15
 
1.5%
singh 12
 
1.2%
cohen 10
 
1.0%
flaherty 10
 
1.0%
hennessy 9
 
0.9%
elphick 9
 
0.9%
douvres 8
 
0.8%
management 7
 
0.7%
lin 7
 
0.7%
de 6
 
0.6%
Other values (637) 924
90.9%
2023-12-09T22:31:12.247794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 694
 
10.5%
A 646
 
9.8%
R 572
 
8.7%
N 522
 
7.9%
O 469
 
7.1%
I 459
 
6.9%
S 394
 
6.0%
L 341
 
5.2%
T 294
 
4.4%
H 293
 
4.4%
Other values (20) 1927
29.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6582
99.6%
Space Separator 17
 
0.3%
Dash Punctuation 9
 
0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 694
 
10.5%
A 646
 
9.8%
R 572
 
8.7%
N 522
 
7.9%
O 469
 
7.1%
I 459
 
7.0%
S 394
 
6.0%
L 341
 
5.2%
T 294
 
4.5%
H 293
 
4.5%
Other values (16) 1898
28.8%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
' 1
33.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6582
99.6%
Common 29
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 694
 
10.5%
A 646
 
9.8%
R 572
 
8.7%
N 522
 
7.9%
O 469
 
7.1%
I 459
 
7.0%
S 394
 
6.0%
L 341
 
5.2%
T 294
 
4.5%
H 293
 
4.5%
Other values (16) 1898
28.8%
Common
ValueCountFrequency (%)
17
58.6%
- 9
31.0%
. 2
 
6.9%
' 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6611
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 694
 
10.5%
A 646
 
9.8%
R 572
 
8.7%
N 522
 
7.9%
O 469
 
7.1%
I 459
 
6.9%
S 394
 
6.0%
L 341
 
5.2%
T 294
 
4.4%
H 293
 
4.4%
Other values (20) 1927
29.1%

owner_title
Text

MISSING 

Distinct45
Distinct (%)20.4%
Missing779
Missing (%)77.9%
Memory size38.3 KiB
2023-12-09T22:31:12.478593image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length20
Median length5
Mean length7.316742081
Min length2

Characters and Unicode

Total characters1617
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)12.7%

Sample

1st rowAgent
2nd rowAgent
3rd rowExecutive VP
4th rowAgent
5th rowEVP
ValueCountFrequency (%)
agent 143
51.3%
rep 25
 
9.0%
owner 15
 
5.4%
contract 14
 
5.0%
president 13
 
4.7%
vice 10
 
3.6%
manager 10
 
3.6%
management 8
 
2.9%
vp 4
 
1.4%
property 4
 
1.4%
Other values (21) 33
 
11.8%
2023-12-09T22:31:12.844735image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 170
 
10.5%
E 147
 
9.1%
e 128
 
7.9%
N 125
 
7.7%
T 111
 
6.9%
n 107
 
6.6%
G 103
 
6.4%
t 100
 
6.2%
r 68
 
4.2%
g 68
 
4.2%
Other values (33) 490
30.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 877
54.2%
Lowercase Letter 679
42.0%
Space Separator 58
 
3.6%
Other Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 128
18.9%
n 107
15.8%
t 100
14.7%
r 68
10.0%
g 68
10.0%
a 40
 
5.9%
o 31
 
4.6%
p 30
 
4.4%
c 22
 
3.2%
i 21
 
3.1%
Other values (12) 64
9.4%
Uppercase Letter
ValueCountFrequency (%)
A 170
19.4%
E 147
16.8%
N 125
14.3%
T 111
12.7%
G 103
11.7%
R 44
 
5.0%
C 29
 
3.3%
P 28
 
3.2%
M 27
 
3.1%
O 22
 
2.5%
Other values (8) 71
8.1%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1556
96.2%
Common 61
 
3.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 170
 
10.9%
E 147
 
9.4%
e 128
 
8.2%
N 125
 
8.0%
T 111
 
7.1%
n 107
 
6.9%
G 103
 
6.6%
t 100
 
6.4%
r 68
 
4.4%
g 68
 
4.4%
Other values (30) 429
27.6%
Common
ValueCountFrequency (%)
58
95.1%
, 2
 
3.3%
. 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1617
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 170
 
10.5%
E 147
 
9.1%
e 128
 
7.9%
N 125
 
7.7%
T 111
 
6.9%
n 107
 
6.6%
G 103
 
6.4%
t 100
 
6.2%
r 68
 
4.2%
g 68
 
4.2%
Other values (33) 490
30.3%
Distinct537
Distinct (%)54.0%
Missing6
Missing (%)0.6%
Memory size72.6 KiB
2023-12-09T22:31:13.209697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length29
Mean length17.43259557
Min length2

Characters and Unicode

Total characters17328
Distinct characters64
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique424 ?
Unique (%)42.7%

Sample

1st rowNYC OCME
2nd rowEMPIRE STATE REALTY TRUST
3rd rowALMA INDUSTRIES
4th rowELMCOR YOUTH & ADULT ACTIVITIES, IN
5th rowHALSTEAD MGMT
ValueCountFrequency (%)
llc 177
 
6.3%
pr 171
 
6.1%
management 86
 
3.1%
inc 84
 
3.0%
corp 62
 
2.2%
realty 53
 
1.9%
the 41
 
1.5%
group 38
 
1.4%
37
 
1.3%
properties 32
 
1.1%
Other values (825) 2019
72.1%
2023-12-09T22:31:13.751745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1806
 
10.4%
E 1597
 
9.2%
R 1364
 
7.9%
T 1190
 
6.9%
O 1105
 
6.4%
N 1101
 
6.4%
A 1087
 
6.3%
L 892
 
5.1%
I 879
 
5.1%
S 862
 
5.0%
Other values (54) 5445
31.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 14879
85.9%
Space Separator 1806
 
10.4%
Decimal Number 302
 
1.7%
Other Punctuation 272
 
1.6%
Lowercase Letter 42
 
0.2%
Dash Punctuation 21
 
0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1597
10.7%
R 1364
 
9.2%
T 1190
 
8.0%
O 1105
 
7.4%
N 1101
 
7.4%
A 1087
 
7.3%
L 892
 
6.0%
I 879
 
5.9%
S 862
 
5.8%
C 855
 
5.7%
Other values (16) 3947
26.5%
Lowercase Letter
ValueCountFrequency (%)
r 6
14.3%
e 6
14.3%
a 5
11.9%
t 4
9.5%
n 4
9.5%
m 3
7.1%
o 3
7.1%
p 2
 
4.8%
l 1
 
2.4%
s 1
 
2.4%
Other values (7) 7
16.7%
Decimal Number
ValueCountFrequency (%)
1 56
18.5%
0 46
15.2%
3 39
12.9%
5 37
12.3%
2 34
11.3%
4 24
7.9%
7 22
 
7.3%
8 22
 
7.3%
6 11
 
3.6%
9 11
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 123
45.2%
, 88
32.4%
& 47
 
17.3%
/ 7
 
2.6%
' 4
 
1.5%
; 2
 
0.7%
@ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14921
86.1%
Common 2407
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1597
10.7%
R 1364
 
9.1%
T 1190
 
8.0%
O 1105
 
7.4%
N 1101
 
7.4%
A 1087
 
7.3%
L 892
 
6.0%
I 879
 
5.9%
S 862
 
5.8%
C 855
 
5.7%
Other values (33) 3989
26.7%
Common
ValueCountFrequency (%)
1806
75.0%
. 123
 
5.1%
, 88
 
3.7%
1 56
 
2.3%
& 47
 
2.0%
0 46
 
1.9%
3 39
 
1.6%
5 37
 
1.5%
2 34
 
1.4%
4 24
 
1.0%
Other values (11) 107
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17328
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1806
 
10.4%
E 1597
 
9.2%
R 1364
 
7.9%
T 1190
 
6.9%
O 1105
 
6.4%
N 1101
 
6.4%
A 1087
 
6.3%
L 892
 
5.1%
I 879
 
5.1%
S 862
 
5.0%
Other values (54) 5445
31.4%

owner_address
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

owner_city
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

owner_state
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

owner_zip
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size64.0 KiB
2023-12-09T22:31:13.928287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length21
Median length7
Mean length8.381
Min length5

Characters and Unicode

Total characters8381
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCity owned Non- NYCHA
2nd rowPrivate
3rd rowPrivate
4th rowPrivate-Tax Exempt
5th rowPrivate
ValueCountFrequency (%)
private 849
73.4%
private-tax 111
 
9.6%
exempt 111
 
9.6%
nycha 38
 
3.3%
city 15
 
1.3%
owned 15
 
1.3%
non 15
 
1.3%
state 2
 
0.2%
2023-12-09T22:31:14.224726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1090
13.0%
e 1088
13.0%
a 1073
12.8%
i 975
11.6%
P 960
11.5%
r 960
11.5%
v 960
11.5%
x 222
 
2.6%
156
 
1.9%
- 126
 
1.5%
Other values (15) 771
9.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6695
79.9%
Uppercase Letter 1404
 
16.8%
Space Separator 156
 
1.9%
Dash Punctuation 126
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1090
16.3%
e 1088
16.3%
a 1073
16.0%
i 975
14.6%
r 960
14.3%
v 960
14.3%
x 222
 
3.3%
p 111
 
1.7%
m 111
 
1.7%
o 30
 
0.4%
Other values (4) 75
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
P 960
68.4%
E 111
 
7.9%
T 111
 
7.9%
N 53
 
3.8%
C 53
 
3.8%
Y 38
 
2.7%
H 38
 
2.7%
A 38
 
2.7%
S 2
 
0.1%
Space Separator
ValueCountFrequency (%)
156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8099
96.6%
Common 282
 
3.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1090
13.5%
e 1088
13.4%
a 1073
13.2%
i 975
12.0%
P 960
11.9%
r 960
11.9%
v 960
11.9%
x 222
 
2.7%
p 111
 
1.4%
m 111
 
1.4%
Other values (13) 549
6.8%
Common
ValueCountFrequency (%)
156
55.3%
- 126
44.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1090
13.0%
e 1088
13.0%
a 1073
12.8%
i 975
11.6%
P 960
11.5%
r 960
11.5%
v 960
11.5%
x 222
 
2.6%
156
 
1.9%
- 126
 
1.5%
Other values (15) 771
9.2%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size296.6 KiB
2023-12-09T22:31:14.464477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length250
Median length250
Mean length246.541
Min length99

Characters and Unicode

Total characters246541
Distinct characters50
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThe scope of work is exempt from the asbestos requirement (Reg. promulgated by the NYC DEP (15RCNY 1-23(b)) or is an alteration to a building constructed pursuant to plans submitted for approval on or after April 1, 1987, in accordance with 28-106.1.
2nd rowThe scope of work is exempt from the asbestos requirement (Reg. promulgated by the NYC DEP (15RCNY 1-23(b)) or is an alteration to a building constructed pursuant to plans submitted for approval on or after April 1, 1987, in accordance with 28-106.1.
3rd rowThe scope of work is exempt from the asbestos requirement (Reg. promulgated by the NYC DEP (15RCNY 1-23(b)) or is an alteration to a building constructed pursuant to plans submitted for approval on or after April 1, 1987, in accordance with 28-106.1.
4th rowThe scope of work is exempt from the asbestos requirement (Reg. promulgated by the NYC DEP (15RCNY 1-23(b)) or is an alteration to a building constructed pursuant to plans submitted for approval on or after April 1, 1987, in accordance with 28-106.1.
5th rowThe scope of work is exempt from the asbestos requirement (Reg. promulgated by the NYC DEP (15RCNY 1-23(b)) or is an alteration to a building constructed pursuant to plans submitted for approval on or after April 1, 1987, in accordance with 28-106.1.
ValueCountFrequency (%)
the 3000
 
7.2%
is 1974
 
4.8%
or 1952
 
4.7%
to 1952
 
4.7%
of 1024
 
2.5%
dep 1011
 
2.4%
work 1000
 
2.4%
asbestos 1000
 
2.4%
in 1000
 
2.4%
scope 1000
 
2.4%
Other values (38) 26542
64.0%
2023-12-09T22:31:14.840315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40455
16.4%
e 16895
 
6.9%
t 16760
 
6.8%
o 15804
 
6.4%
r 14771
 
6.0%
a 12810
 
5.2%
s 9928
 
4.0%
n 9878
 
4.0%
i 9878
 
4.0%
p 7843
 
3.2%
Other values (40) 91519
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 165823
67.3%
Space Separator 40455
 
16.4%
Decimal Number 15616
 
6.3%
Uppercase Letter 12900
 
5.2%
Other Punctuation 4915
 
2.0%
Open Punctuation 2928
 
1.2%
Dash Punctuation 1952
 
0.8%
Close Punctuation 1952
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 16895
 
10.2%
t 16760
 
10.1%
o 15804
 
9.5%
r 14771
 
8.9%
a 12810
 
7.7%
s 9928
 
6.0%
n 9878
 
6.0%
i 9878
 
6.0%
p 7843
 
4.7%
u 6880
 
4.1%
Other values (15) 44376
26.8%
Decimal Number
ValueCountFrequency (%)
1 5856
37.5%
2 1952
 
12.5%
8 1952
 
12.5%
5 976
 
6.2%
3 976
 
6.2%
9 976
 
6.2%
7 976
 
6.2%
0 976
 
6.2%
6 976
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
C 1987
15.4%
Y 1976
15.3%
N 1976
15.3%
R 1952
15.1%
D 1011
7.8%
E 1011
7.8%
P 1011
7.8%
T 1000
7.8%
A 976
7.6%
Other Punctuation
ValueCountFrequency (%)
. 2952
60.1%
, 1952
39.7%
# 11
 
0.2%
Space Separator
ValueCountFrequency (%)
40455
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2928
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1952
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1952
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 178723
72.5%
Common 67818
 
27.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 16895
 
9.5%
t 16760
 
9.4%
o 15804
 
8.8%
r 14771
 
8.3%
a 12810
 
7.2%
s 9928
 
5.6%
n 9878
 
5.5%
i 9878
 
5.5%
p 7843
 
4.4%
u 6880
 
3.8%
Other values (24) 57276
32.0%
Common
ValueCountFrequency (%)
40455
59.7%
1 5856
 
8.6%
. 2952
 
4.4%
( 2928
 
4.3%
2 1952
 
2.9%
- 1952
 
2.9%
) 1952
 
2.9%
, 1952
 
2.9%
8 1952
 
2.9%
5 976
 
1.4%
Other values (6) 4891
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 246541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40455
16.4%
e 16895
 
6.9%
t 16760
 
6.8%
o 15804
 
6.4%
r 14771
 
6.0%
a 12810
 
5.2%
s 9928
 
4.0%
n 9878
 
4.0%
i 9878
 
4.0%
p 7843
 
3.2%
Other values (40) 91519
37.1%

depacp5controlno
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing988
Missing (%)98.8%
Memory size31.7 KiB
2023-12-09T22:31:15.050606image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.916666667
Min length6

Characters and Unicode

Total characters83
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row2794557
2nd row1383574
3rd row1390185
4th row1828934
5th row1538785
ValueCountFrequency (%)
1571584 1
8.3%
1326488 1
8.3%
1383574 1
8.3%
2794557 1
8.3%
4639118 1
8.3%
3980705 1
8.3%
1390185 1
8.3%
1346362 1
8.3%
123456 1
8.3%
1538785 1
8.3%
Other values (2) 2
16.7%
2023-12-09T22:31:15.381220image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
15.7%
8 13
15.7%
3 12
14.5%
5 10
12.0%
4 9
10.8%
7 6
7.2%
2 6
7.2%
6 6
7.2%
9 5
 
6.0%
0 3
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
15.7%
8 13
15.7%
3 12
14.5%
5 10
12.0%
4 9
10.8%
7 6
7.2%
2 6
7.2%
6 6
7.2%
9 5
 
6.0%
0 3
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 83
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
15.7%
8 13
15.7%
3 12
14.5%
5 10
12.0%
4 9
10.8%
7 6
7.2%
2 6
7.2%
6 6
7.2%
9 5
 
6.0%
0 3
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
15.7%
8 13
15.7%
3 12
14.5%
5 10
12.0%
4 9
10.8%
7 6
7.2%
2 6
7.2%
6 6
7.2%
9 5
 
6.0%
0 3
 
3.6%
Distinct708
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size341.6 KiB
2023-12-09T22:31:15.743136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length510
Median length443
Mean length292.663
Min length19

Characters and Unicode

Total characters292663
Distinct characters81
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique628 ?
Unique (%)62.8%

Sample

1st rowModification to the existing controller to install Door Position Monitoring System as per requirements of ASME A17.3 of 2015, as modified by 2022 NYC Building Code, Appendix K, Chapter K3, Section 3.10.12. All tests and inspections must be performed as per 1RCNY Section 101-02 and 101-07.
2nd rowFurnish and install one (1) new MRL elevator as per attached drawings, Plan # N1T529 - P2 - Existing Building. All work to comply with ASME A17.1-2005S, as modified by Appendix K and Chapter 30 of 2014 BC - Section 2. All test / inspections to be conducted in the presence of NYC Department of Buildings Elevator Inspector.
3rd rowAll work to comply with ASME A17.1-2013, Part 2, Safety Code for Elevators and Escalators as modified by Appendix K, Chapter K1 and Chapter 30 of 2022 BC. All inspections during the progress and upon completion of the work to be performed as per OPPN #26/90. Filing this application to Furnish and Install New Door Lock Monitoring
4th rowFurnish and install components and software providing Door Monitor Circuitry to existing controller. -All work to comply with ASME A17.1-2000 with supplement A17.1a-02 and A17.10-03 as modified by Appendix K, Section 3.10.12 and Chapter 30 of 2014 BC. All tests and inspections must be performed as per 1RCNY Section 101-02 and 101-07.
5th rowFurnish and install modifications to the existing controller that will enable the controller to comply with the NYC Appendix K Section 3.10.12 door positioning requirements. All inspections/tests to be performed during the progress and upon completion of the indicated work by the applicant per PPN #26/90
ValueCountFrequency (%)
and 2212
 
4.8%
of 1918
 
4.1%
to 1819
 
3.9%
the 1751
 
3.8%
all 986
 
2.1%
nyc 929
 
2.0%
as 858
 
1.8%
with 802
 
1.7%
per 768
 
1.6%
be 750
 
1.6%
Other values (1819) 33754
72.5%
2023-12-09T22:31:16.279815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46786
 
16.0%
e 18693
 
6.4%
o 15303
 
5.2%
t 14786
 
5.1%
n 13710
 
4.7%
i 11925
 
4.1%
r 10983
 
3.8%
a 10479
 
3.6%
s 10231
 
3.5%
l 8402
 
2.9%
Other values (71) 131365
44.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 161162
55.1%
Uppercase Letter 54676
 
18.7%
Space Separator 46786
 
16.0%
Decimal Number 18125
 
6.2%
Other Punctuation 9476
 
3.2%
Dash Punctuation 1136
 
0.4%
Close Punctuation 652
 
0.2%
Open Punctuation 650
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 18693
11.6%
o 15303
 
9.5%
t 14786
 
9.2%
n 13710
 
8.5%
i 11925
 
7.4%
r 10983
 
6.8%
a 10479
 
6.5%
s 10231
 
6.3%
l 8402
 
5.2%
d 7466
 
4.6%
Other values (16) 39184
24.3%
Uppercase Letter
ValueCountFrequency (%)
A 5981
10.9%
E 5662
 
10.4%
N 4735
 
8.7%
C 3915
 
7.2%
S 3766
 
6.9%
I 3674
 
6.7%
T 3585
 
6.6%
O 3259
 
6.0%
R 2843
 
5.2%
P 2842
 
5.2%
Other values (16) 14414
26.4%
Other Punctuation
ValueCountFrequency (%)
. 5355
56.5%
, 1563
 
16.5%
/ 1095
 
11.6%
' 786
 
8.3%
# 349
 
3.7%
* 198
 
2.1%
: 106
 
1.1%
; 11
 
0.1%
% 10
 
0.1%
! 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 4536
25.0%
1 4402
24.3%
2 3214
17.7%
3 2041
11.3%
7 1286
 
7.1%
4 744
 
4.1%
6 569
 
3.1%
9 524
 
2.9%
8 477
 
2.6%
5 332
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 590
90.5%
] 61
 
9.4%
} 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 569
87.5%
[ 73
 
11.2%
{ 8
 
1.2%
Space Separator
ValueCountFrequency (%)
46786
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 215838
73.7%
Common 76825
 
26.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 18693
 
8.7%
o 15303
 
7.1%
t 14786
 
6.9%
n 13710
 
6.4%
i 11925
 
5.5%
r 10983
 
5.1%
a 10479
 
4.9%
s 10231
 
4.7%
l 8402
 
3.9%
d 7466
 
3.5%
Other values (42) 93860
43.5%
Common
ValueCountFrequency (%)
46786
60.9%
. 5355
 
7.0%
0 4536
 
5.9%
1 4402
 
5.7%
2 3214
 
4.2%
3 2041
 
2.7%
, 1563
 
2.0%
7 1286
 
1.7%
- 1136
 
1.5%
/ 1095
 
1.4%
Other values (19) 5411
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292663
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46786
 
16.0%
e 18693
 
6.4%
o 15303
 
5.2%
t 14786
 
5.1%
n 13710
 
4.7%
i 11925
 
4.1%
r 10983
 
3.8%
a 10479
 
3.6%
s 10231
 
3.5%
l 8402
 
2.9%
Other values (71) 131365
44.9%
Distinct71
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size76.3 KiB
2023-12-09T22:31:16.544356image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length32
Mean length20.983
Min length16

Characters and Unicode

Total characters20983
Distinct characters51
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)3.2%

Sample

1st rowTRUMBULL INSURANCE COMP
2nd rowNATIONAL UNION FIRE INS
3rd rowLLOYDS OF LONDON
4th rowHDI GLOBAL INSURANCE CO
5th rowGREAT AMERICAN INS
ValueCountFrequency (%)
ins 511
14.3%
co 457
12.8%
american 424
11.9%
great 413
11.6%
insurance 345
 
9.7%
zurich 198
 
5.5%
88
 
2.5%
fire 86
 
2.4%
e 81
 
2.3%
s 81
 
2.3%
Other values (90) 889
24.9%
2023-12-09T22:31:16.934310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2573
12.3%
N 2211
10.5%
A 2110
10.1%
I 1984
9.5%
C 1778
8.5%
R 1746
8.3%
E 1592
 
7.6%
S 1159
 
5.5%
O 1076
 
5.1%
T 674
 
3.2%
Other values (41) 4080
19.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 18101
86.3%
Space Separator 2573
 
12.3%
Lowercase Letter 192
 
0.9%
Other Punctuation 116
 
0.6%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 2211
12.2%
A 2110
11.7%
I 1984
11.0%
C 1778
9.8%
R 1746
9.6%
E 1592
8.8%
S 1159
 
6.4%
O 1076
 
5.9%
T 674
 
3.7%
U 674
 
3.7%
Other values (15) 3097
17.1%
Lowercase Letter
ValueCountFrequency (%)
a 25
13.0%
e 24
12.5%
n 23
12.0%
r 20
10.4%
c 12
 
6.2%
y 12
 
6.2%
s 10
 
5.2%
u 10
 
5.2%
i 9
 
4.7%
d 8
 
4.2%
Other values (10) 39
20.3%
Other Punctuation
ValueCountFrequency (%)
& 95
81.9%
' 9
 
7.8%
/ 8
 
6.9%
. 4
 
3.4%
Space Separator
ValueCountFrequency (%)
2573
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18293
87.2%
Common 2690
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2211
12.1%
A 2110
11.5%
I 1984
10.8%
C 1778
9.7%
R 1746
9.5%
E 1592
8.7%
S 1159
 
6.3%
O 1076
 
5.9%
T 674
 
3.7%
U 674
 
3.7%
Other values (35) 3289
18.0%
Common
ValueCountFrequency (%)
2573
95.7%
& 95
 
3.5%
' 9
 
0.3%
/ 8
 
0.3%
. 4
 
0.1%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2573
12.3%
N 2211
10.5%
A 2110
10.1%
I 1984
9.5%
C 1778
8.5%
R 1746
8.3%
E 1592
 
7.6%
S 1159
 
5.5%
O 1076
 
5.1%
T 674
 
3.2%
Other values (41) 4080
19.4%
Distinct150
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
2023-12-09T22:31:17.240782image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length12
Mean length11.966
Min length5

Characters and Unicode

Total characters11966
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)6.7%

Sample

1st row12SBAVH0855
2nd row3980241
3rd rowB1749S230072
4th rowGLD5668800/GLD
5th rowGLP130335603
ValueCountFrequency (%)
glo644543529 90
 
8.8%
glo644543530 45
 
4.4%
glp130335603 43
 
4.2%
gl0644543532 35
 
3.4%
csu0093329 34
 
3.3%
o2cset10004 33
 
3.2%
glp132436702 31
 
3.0%
glo644543531 31
 
3.0%
glp132481402 29
 
2.8%
glo644543528 29
 
2.8%
Other values (149) 625
61.0%
2023-12-09T22:31:17.718943image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1524
12.7%
3 1440
12.0%
4 1246
10.4%
1 1012
8.5%
2 842
 
7.0%
6 836
 
7.0%
5 825
 
6.9%
G 729
 
6.1%
L 723
 
6.0%
7 454
 
3.8%
Other values (27) 2335
19.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8864
74.1%
Uppercase Letter 3020
 
25.2%
Dash Punctuation 44
 
0.4%
Space Separator 25
 
0.2%
Other Punctuation 13
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 729
24.1%
L 723
23.9%
P 396
13.1%
O 286
 
9.5%
C 144
 
4.8%
S 118
 
3.9%
E 95
 
3.1%
A 77
 
2.5%
B 73
 
2.4%
D 67
 
2.2%
Other values (14) 312
10.3%
Decimal Number
ValueCountFrequency (%)
0 1524
17.2%
3 1440
16.2%
4 1246
14.1%
1 1012
11.4%
2 842
9.5%
6 836
9.4%
5 825
9.3%
7 454
 
5.1%
9 396
 
4.5%
8 289
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8946
74.8%
Latin 3020
 
25.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 729
24.1%
L 723
23.9%
P 396
13.1%
O 286
 
9.5%
C 144
 
4.8%
S 118
 
3.9%
E 95
 
3.1%
A 77
 
2.5%
B 73
 
2.4%
D 67
 
2.2%
Other values (14) 312
10.3%
Common
ValueCountFrequency (%)
0 1524
17.0%
3 1440
16.1%
4 1246
13.9%
1 1012
11.3%
2 842
9.4%
6 836
9.3%
5 825
9.2%
7 454
 
5.1%
9 396
 
4.4%
8 289
 
3.2%
Other values (3) 82
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11966
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1524
12.7%
3 1440
12.0%
4 1246
10.4%
1 1012
8.5%
2 842
 
7.0%
6 836
 
7.0%
5 825
 
6.9%
G 729
 
6.1%
L 723
 
6.0%
7 454
 
3.8%
Other values (27) 2335
19.5%
Distinct134
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T22:31:18.053497image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)5.0%

Sample

1st row2023-06-22T00:00:00.000
2nd row2022-12-01T00:00:00.000
3rd row2024-03-01T00:00:00.000
4th row2021-10-01T00:00:00.000
5th row2020-12-10T00:00:00.000
ValueCountFrequency (%)
2020-01-01t00:00:00.000 90
 
9.0%
2021-01-01t00:00:00.000 49
 
4.9%
2020-12-10t00:00:00.000 43
 
4.3%
2022-01-01t00:00:00.000 31
 
3.1%
2020-03-08t00:00:00.000 31
 
3.1%
2020-07-01t00:00:00.000 30
 
3.0%
2019-01-01t00:00:00.000 29
 
2.9%
2021-05-24t00:00:00.000 27
 
2.7%
2022-03-08t00:00:00.000 26
 
2.6%
2020-05-24t00:00:00.000 25
 
2.5%
Other values (124) 619
61.9%
2023-12-09T22:31:18.504190image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11848
51.5%
2 2421
 
10.5%
- 2000
 
8.7%
: 2000
 
8.7%
1 1519
 
6.6%
T 1000
 
4.3%
. 1000
 
4.3%
3 370
 
1.6%
4 291
 
1.3%
9 163
 
0.7%
Other values (4) 388
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11848
69.7%
2 2421
 
14.2%
1 1519
 
8.9%
3 370
 
2.2%
4 291
 
1.7%
9 163
 
1.0%
5 145
 
0.9%
8 108
 
0.6%
6 71
 
0.4%
7 64
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11848
53.9%
2 2421
 
11.0%
- 2000
 
9.1%
: 2000
 
9.1%
1 1519
 
6.9%
. 1000
 
4.5%
3 370
 
1.7%
4 291
 
1.3%
9 163
 
0.7%
5 145
 
0.7%
Other values (3) 243
 
1.1%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11848
51.5%
2 2421
 
10.5%
- 2000
 
8.7%
: 2000
 
8.7%
1 1519
 
6.6%
T 1000
 
4.3%
. 1000
 
4.3%
3 370
 
1.6%
4 291
 
1.3%
9 163
 
0.7%
Other values (4) 388
 
1.7%
Distinct72
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size76.3 KiB
2023-12-09T22:31:18.773648image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length44
Mean length20.963
Min length5

Characters and Unicode

Total characters20963
Distinct characters64
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)2.7%

Sample

1st rowTWIN CITY FIRE INS COMP
2nd rowAIU INSURANCE COMPANY
3rd rowTRAVELERS INDEMNITY OF CT
4th rowINDEMNITY INS CO
5th rowNEW YORK STATE INS FUND
ValueCountFrequency (%)
ins 623
16.5%
co 330
 
8.8%
new 275
 
7.3%
american 234
 
6.2%
zurich 233
 
6.2%
state 230
 
6.1%
york 226
 
6.0%
fund 220
 
5.8%
insurance 176
 
4.7%
company 132
 
3.5%
Other values (80) 1086
28.8%
2023-12-09T22:31:19.195712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2765
13.2%
N 2246
 
10.7%
I 1930
 
9.2%
E 1440
 
6.9%
A 1436
 
6.9%
C 1292
 
6.2%
S 1270
 
6.1%
R 1178
 
5.6%
O 959
 
4.6%
T 790
 
3.8%
Other values (54) 5657
27.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 17035
81.3%
Space Separator 2765
 
13.2%
Lowercase Letter 1047
 
5.0%
Other Punctuation 69
 
0.3%
Decimal Number 29
 
0.1%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 2246
13.2%
I 1930
11.3%
E 1440
 
8.5%
A 1436
 
8.4%
C 1292
 
7.6%
S 1270
 
7.5%
R 1178
 
6.9%
O 959
 
5.6%
T 790
 
4.6%
U 767
 
4.5%
Other values (15) 3727
21.9%
Lowercase Letter
ValueCountFrequency (%)
n 154
14.7%
a 132
12.6%
r 116
11.1%
o 109
10.4%
e 95
9.1%
s 74
7.1%
c 56
 
5.3%
u 55
 
5.3%
t 52
 
5.0%
p 50
 
4.8%
Other values (12) 154
14.7%
Decimal Number
ValueCountFrequency (%)
0 6
20.7%
2 5
17.2%
6 5
17.2%
3 4
13.8%
1 4
13.8%
5 3
10.3%
9 1
 
3.4%
4 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
& 42
60.9%
/ 8
 
11.6%
. 7
 
10.1%
' 6
 
8.7%
, 3
 
4.3%
; 3
 
4.3%
Space Separator
ValueCountFrequency (%)
2765
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18082
86.3%
Common 2881
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2246
12.4%
I 1930
10.7%
E 1440
 
8.0%
A 1436
 
7.9%
C 1292
 
7.1%
S 1270
 
7.0%
R 1178
 
6.5%
O 959
 
5.3%
T 790
 
4.4%
U 767
 
4.2%
Other values (37) 4774
26.4%
Common
ValueCountFrequency (%)
2765
96.0%
& 42
 
1.5%
( 9
 
0.3%
) 9
 
0.3%
/ 8
 
0.3%
. 7
 
0.2%
0 6
 
0.2%
' 6
 
0.2%
2 5
 
0.2%
6 5
 
0.2%
Other values (7) 19
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20963
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2765
13.2%
N 2246
 
10.7%
I 1930
 
9.2%
E 1440
 
6.9%
A 1436
 
6.9%
C 1292
 
6.2%
S 1270
 
6.1%
R 1178
 
5.6%
O 959
 
4.6%
T 790
 
3.8%
Other values (54) 5657
27.0%
Distinct143
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
2023-12-09T22:31:19.544806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length25
Median length11
Mean length11.035
Min length5

Characters and Unicode

Total characters11035
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)6.6%

Sample

1st row12WECKZ9652
2nd rowWC065885882
3rd rowUB4W99928723
4th rowWLRC67462671
5th rowG2318 442-7
ValueCountFrequency (%)
wc666818728 90
 
6.3%
442-7 85
 
6.0%
679-1 81
 
5.7%
g1487 80
 
5.6%
g2318 44
 
3.1%
wc666818729 44
 
3.1%
z2318 41
 
2.9%
sw5wc00167-191 40
 
2.8%
wc666818731 37
 
2.6%
qwc3001178 35
 
2.5%
Other values (198) 845
59.4%
2023-12-09T22:31:20.050335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1268
11.5%
6 1169
10.6%
8 1044
9.5%
0 925
 
8.4%
2 916
 
8.3%
7 855
 
7.7%
W 665
 
6.0%
3 580
 
5.3%
4 556
 
5.0%
C 544
 
4.9%
Other values (28) 2513
22.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8258
74.8%
Uppercase Letter 1951
 
17.7%
Space Separator 422
 
3.8%
Dash Punctuation 402
 
3.6%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W 665
34.1%
C 544
27.9%
G 174
 
8.9%
Q 86
 
4.4%
Z 84
 
4.3%
L 65
 
3.3%
V 55
 
2.8%
R 55
 
2.8%
S 50
 
2.6%
B 27
 
1.4%
Other values (14) 146
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 1268
15.4%
6 1169
14.2%
8 1044
12.6%
0 925
11.2%
2 916
11.1%
7 855
10.4%
3 580
7.0%
4 556
6.7%
9 519
6.3%
5 426
 
5.2%
Space Separator
ValueCountFrequency (%)
422
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 402
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9084
82.3%
Latin 1951
 
17.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 665
34.1%
C 544
27.9%
G 174
 
8.9%
Q 86
 
4.4%
Z 84
 
4.3%
L 65
 
3.3%
V 55
 
2.8%
R 55
 
2.8%
S 50
 
2.6%
B 27
 
1.4%
Other values (14) 146
 
7.5%
Common
ValueCountFrequency (%)
1 1268
14.0%
6 1169
12.9%
8 1044
11.5%
0 925
10.2%
2 916
10.1%
7 855
9.4%
3 580
6.4%
4 556
6.1%
9 519
5.7%
5 426
 
4.7%
Other values (4) 826
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11035
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1268
11.5%
6 1169
10.6%
8 1044
9.5%
0 925
 
8.4%
2 916
 
8.3%
7 855
 
7.7%
W 665
 
6.0%
3 580
 
5.3%
4 556
 
5.0%
C 544
 
4.9%
Other values (28) 2513
22.8%
Distinct99
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T22:31:20.362835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)3.6%

Sample

1st row2023-06-22T00:00:00.000
2nd row2022-12-01T00:00:00.000
3rd row2024-03-01T00:00:00.000
4th row2021-10-01T00:00:00.000
5th row2020-04-01T00:00:00.000
ValueCountFrequency (%)
2020-01-01t00:00:00.000 101
 
10.1%
2021-01-01t00:00:00.000 84
 
8.4%
2020-04-01t00:00:00.000 75
 
7.5%
2022-01-01t00:00:00.000 60
 
6.0%
2021-04-01t00:00:00.000 51
 
5.1%
2022-04-01t00:00:00.000 38
 
3.8%
2019-01-01t00:00:00.000 31
 
3.1%
2024-01-01t00:00:00.000 31
 
3.1%
2024-04-01t00:00:00.000 30
 
3.0%
2023-01-01t00:00:00.000 30
 
3.0%
Other values (89) 469
46.9%
2023-12-09T22:31:20.794705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11973
52.1%
2 2306
 
10.0%
- 2000
 
8.7%
: 2000
 
8.7%
1 1619
 
7.0%
T 1000
 
4.3%
. 1000
 
4.3%
4 482
 
2.1%
3 242
 
1.1%
5 144
 
0.6%
Other values (4) 234
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11973
70.4%
2 2306
 
13.6%
1 1619
 
9.5%
4 482
 
2.8%
3 242
 
1.4%
5 144
 
0.8%
9 132
 
0.8%
7 59
 
0.3%
6 33
 
0.2%
8 10
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11973
54.4%
2 2306
 
10.5%
- 2000
 
9.1%
: 2000
 
9.1%
1 1619
 
7.4%
. 1000
 
4.5%
4 482
 
2.2%
3 242
 
1.1%
5 144
 
0.7%
9 132
 
0.6%
Other values (3) 102
 
0.5%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11973
52.1%
2 2306
 
10.0%
- 2000
 
8.7%
: 2000
 
8.7%
1 1619
 
7.0%
T 1000
 
4.3%
. 1000
 
4.3%
4 482
 
2.1%
3 242
 
1.1%
5 144
 
0.6%
Other values (4) 234
 
1.0%
Distinct64
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size78.8 KiB
2023-12-09T22:31:21.042661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length44
Median length38
Mean length23.607
Min length5

Characters and Unicode

Total characters23607
Distinct characters53
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)1.9%

Sample

1st rowSHELTERPOINT LIFE INS CO
2nd rowLIBERTY LIFE ASSURANCE
3rd rowTRAVELERS INDEMNITY OF CT
4th rowHARTFORD LIFE AND ACCIDEN
5th rowWESCO INSURANCE COMPANY
ValueCountFrequency (%)
life 765
19.1%
ins 569
14.2%
co 487
12.2%
shelterpoint 295
 
7.4%
insurance 260
 
6.5%
first 222
 
5.5%
company 218
 
5.4%
unum 206
 
5.1%
wesco 121
 
3.0%
the 88
 
2.2%
Other values (53) 771
19.3%
2023-12-09T22:31:21.435702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3002
12.7%
I 2305
 
9.8%
N 2064
 
8.7%
E 1988
 
8.4%
S 1689
 
7.2%
O 1246
 
5.3%
C 1227
 
5.2%
L 1192
 
5.0%
R 1135
 
4.8%
T 1098
 
4.7%
Other values (43) 6661
28.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 18951
80.3%
Space Separator 3002
 
12.7%
Lowercase Letter 1630
 
6.9%
Decimal Number 13
 
0.1%
Other Punctuation 11
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 2305
12.2%
N 2064
10.9%
E 1988
10.5%
S 1689
8.9%
O 1246
 
6.6%
C 1227
 
6.5%
L 1192
 
6.3%
R 1135
 
6.0%
T 1098
 
5.8%
F 1022
 
5.4%
Other values (12) 3985
21.0%
Lowercase Letter
ValueCountFrequency (%)
n 234
14.4%
e 208
12.8%
a 138
8.5%
i 125
 
7.7%
o 122
 
7.5%
r 120
 
7.4%
t 107
 
6.6%
c 94
 
5.8%
p 75
 
4.6%
f 64
 
3.9%
Other values (9) 343
21.0%
Decimal Number
ValueCountFrequency (%)
4 2
15.4%
1 2
15.4%
7 2
15.4%
9 2
15.4%
0 2
15.4%
8 1
7.7%
2 1
7.7%
3 1
7.7%
Other Punctuation
ValueCountFrequency (%)
. 9
81.8%
, 1
 
9.1%
& 1
 
9.1%
Space Separator
ValueCountFrequency (%)
3002
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20581
87.2%
Common 3026
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 2305
11.2%
N 2064
 
10.0%
E 1988
 
9.7%
S 1689
 
8.2%
O 1246
 
6.1%
C 1227
 
6.0%
L 1192
 
5.8%
R 1135
 
5.5%
T 1098
 
5.3%
F 1022
 
5.0%
Other values (31) 5615
27.3%
Common
ValueCountFrequency (%)
3002
99.2%
. 9
 
0.3%
4 2
 
0.1%
1 2
 
0.1%
7 2
 
0.1%
9 2
 
0.1%
0 2
 
0.1%
, 1
 
< 0.1%
8 1
 
< 0.1%
2 1
 
< 0.1%
Other values (2) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23607
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3002
12.7%
I 2305
 
9.8%
N 2064
 
8.7%
E 1988
 
8.4%
S 1689
 
7.2%
O 1246
 
5.3%
C 1227
 
5.2%
L 1192
 
5.0%
R 1135
 
4.8%
T 1098
 
4.7%
Other values (43) 6661
28.2%
Distinct107
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size64.4 KiB
2023-12-09T22:31:21.700934image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length25
Median length23
Mean length8.835
Min length5

Characters and Unicode

Total characters8835
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)5.1%

Sample

1st rowDBL347174
2nd rowGS3890LFO121NY
3rd row234698
4th rowLNY-637421
5th row0911222
ValueCountFrequency (%)
120137 204
18.9%
dbl533745 103
 
9.5%
0911222 83
 
7.7%
dbl602180 45
 
4.2%
dbl 42
 
3.9%
gs3810258966026 35
 
3.2%
c-4347 34
 
3.1%
0911272 33
 
3.0%
gs3890lfo121ny 32
 
3.0%
00975437-0000 29
 
2.7%
Other values (113) 442
40.9%
2023-12-09T22:31:22.117331image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1239
14.0%
1 1128
12.8%
2 924
10.5%
3 774
8.8%
7 666
 
7.5%
9 494
 
5.6%
5 493
 
5.6%
L 463
 
5.2%
D 409
 
4.6%
4 391
 
4.4%
Other values (23) 1854
21.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6819
77.2%
Uppercase Letter 1789
 
20.2%
Dash Punctuation 145
 
1.6%
Space Separator 82
 
0.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 463
25.9%
D 409
22.9%
B 376
21.0%
S 90
 
5.0%
G 90
 
5.0%
N 84
 
4.7%
Y 78
 
4.4%
F 51
 
2.9%
C 43
 
2.4%
O 36
 
2.0%
Other values (11) 69
 
3.9%
Decimal Number
ValueCountFrequency (%)
0 1239
18.2%
1 1128
16.5%
2 924
13.6%
3 774
11.4%
7 666
9.8%
9 494
 
7.2%
5 493
 
7.2%
4 391
 
5.7%
6 358
 
5.3%
8 352
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 145
100.0%
Space Separator
ValueCountFrequency (%)
82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7046
79.8%
Latin 1789
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 463
25.9%
D 409
22.9%
B 376
21.0%
S 90
 
5.0%
G 90
 
5.0%
N 84
 
4.7%
Y 78
 
4.4%
F 51
 
2.9%
C 43
 
2.4%
O 36
 
2.0%
Other values (11) 69
 
3.9%
Common
ValueCountFrequency (%)
0 1239
17.6%
1 1128
16.0%
2 924
13.1%
3 774
11.0%
7 666
9.5%
9 494
 
7.0%
5 493
 
7.0%
4 391
 
5.5%
6 358
 
5.1%
8 352
 
5.0%
Other values (2) 227
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8835
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1239
14.0%
1 1128
12.8%
2 924
10.5%
3 774
8.8%
7 666
 
7.5%
9 494
 
5.6%
5 493
 
5.6%
L 463
 
5.2%
D 409
 
4.6%
4 391
 
4.4%
Other values (23) 1854
21.0%
Distinct96
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2023-12-09T22:31:22.441972image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23000
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)3.2%

Sample

1st row2023-10-07T00:00:00.000
2nd row2023-09-30T00:00:00.000
3rd row2023-12-31T00:00:00.000
4th row2020-12-31T00:00:00.000
5th row2020-12-31T00:00:00.000
ValueCountFrequency (%)
2020-12-31t00:00:00.000 86
 
8.6%
2021-12-31t00:00:00.000 65
 
6.5%
2020-11-01t00:00:00.000 55
 
5.5%
2021-01-01t00:00:00.000 46
 
4.6%
2022-12-31t00:00:00.000 36
 
3.6%
2020-01-01t00:00:00.000 35
 
3.5%
2023-12-31t00:00:00.000 35
 
3.5%
2022-01-01t00:00:00.000 35
 
3.5%
2019-01-01t00:00:00.000 29
 
2.9%
2020-08-01t00:00:00.000 28
 
2.8%
Other values (86) 550
55.0%
2023-12-09T22:31:22.880824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11400
49.6%
2 2529
 
11.0%
- 2000
 
8.7%
: 2000
 
8.7%
1 1710
 
7.4%
T 1000
 
4.3%
. 1000
 
4.3%
3 769
 
3.3%
9 244
 
1.1%
5 129
 
0.6%
Other values (4) 219
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17000
73.9%
Other Punctuation 3000
 
13.0%
Dash Punctuation 2000
 
8.7%
Uppercase Letter 1000
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11400
67.1%
2 2529
 
14.9%
1 1710
 
10.1%
3 769
 
4.5%
9 244
 
1.4%
5 129
 
0.8%
4 104
 
0.6%
8 57
 
0.3%
6 34
 
0.2%
7 24
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 2000
66.7%
. 1000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2000
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22000
95.7%
Latin 1000
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11400
51.8%
2 2529
 
11.5%
- 2000
 
9.1%
: 2000
 
9.1%
1 1710
 
7.8%
. 1000
 
4.5%
3 769
 
3.5%
9 244
 
1.1%
5 129
 
0.6%
4 104
 
0.5%
Other values (3) 115
 
0.5%
Latin
ValueCountFrequency (%)
T 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11400
49.6%
2 2529
 
11.0%
- 2000
 
8.7%
: 2000
 
8.7%
1 1710
 
7.4%
T 1000
 
4.3%
. 1000
 
4.3%
3 769
 
3.3%
9 244
 
1.1%
5 129
 
0.6%
Other values (4) 219
 
1.0%
Distinct587
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Memory size61.0 KiB
2023-12-09T22:31:23.289994image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.369
Min length1

Characters and Unicode

Total characters5369
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique451 ?
Unique (%)45.1%

Sample

1st row24500
2nd row220000
3rd row15000
4th row8000
5th row11100
ValueCountFrequency (%)
10000 52
 
5.2%
20000 40
 
4.0%
14000 22
 
2.2%
7000 15
 
1.5%
8000 12
 
1.2%
15000 10
 
1.0%
5000 10
 
1.0%
4500 10
 
1.0%
3000 9
 
0.9%
7500 8
 
0.8%
Other values (577) 812
81.2%
2023-12-09T22:31:23.815818image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2271
42.3%
1 523
 
9.7%
2 441
 
8.2%
5 394
 
7.3%
4 288
 
5.4%
3 284
 
5.3%
8 275
 
5.1%
7 274
 
5.1%
9 269
 
5.0%
6 254
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5273
98.2%
Other Punctuation 96
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2271
43.1%
1 523
 
9.9%
2 441
 
8.4%
5 394
 
7.5%
4 288
 
5.5%
3 284
 
5.4%
8 275
 
5.2%
7 274
 
5.2%
9 269
 
5.1%
6 254
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5369
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2271
42.3%
1 523
 
9.7%
2 441
 
8.2%
5 394
 
7.3%
4 288
 
5.4%
3 284
 
5.3%
8 275
 
5.1%
7 274
 
5.1%
9 269
 
5.0%
6 254
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2271
42.3%
1 523
 
9.7%
2 441
 
8.2%
5 394
 
7.3%
4 288
 
5.4%
3 284
 
5.3%
8 275
 
5.1%
7 274
 
5.1%
9 269
 
5.0%
6 254
 
4.7%
Distinct237
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size59.8 KiB
2023-12-09T22:31:24.268562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.151
Min length1

Characters and Unicode

Total characters4151
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)14.3%

Sample

1st row0
2nd row2460.1
3rd row318.6
4th row0
5th row287.7
ValueCountFrequency (%)
0 151
 
15.1%
225 151
 
15.1%
308.3 34
 
3.4%
236.2 32
 
3.2%
246.5 31
 
3.1%
267.1 22
 
2.2%
195 22
 
2.2%
318.6 22
 
2.2%
297.1 19
 
1.9%
339.2 18
 
1.8%
Other values (227) 498
49.8%
2023-12-09T22:31:24.842643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 749
18.0%
. 640
15.4%
5 441
10.6%
1 372
9.0%
3 352
8.5%
0 323
7.8%
9 273
 
6.6%
6 268
 
6.5%
4 267
 
6.4%
7 240
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3511
84.6%
Other Punctuation 640
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 749
21.3%
5 441
12.6%
1 372
10.6%
3 352
10.0%
0 323
9.2%
9 273
 
7.8%
6 268
 
7.6%
4 267
 
7.6%
7 240
 
6.8%
8 226
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 640
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4151
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 749
18.0%
. 640
15.4%
5 441
10.6%
1 372
9.0%
3 352
8.5%
0 323
7.8%
9 273
 
6.6%
6 268
 
6.5%
4 267
 
6.4%
7 240
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 749
18.0%
. 640
15.4%
5 441
10.6%
1 372
9.0%
3 352
8.5%
0 323
7.8%
9 273
 
6.6%
6 268
 
6.5%
4 267
 
6.4%
7 240
 
5.8%

no_good_check
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)8.3%
Missing988
Missing (%)98.8%
Memory size31.7 KiB
2023-12-09T22:31:24.960108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters24
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row20
3rd row20
4th row20
5th row20
ValueCountFrequency (%)
20 12
100.0%
2023-12-09T22:31:25.172155image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
50.0%
0 12
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
50.0%
0 12
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
50.0%
0 12
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
50.0%
0 12
50.0%
Distinct263
Distinct (%)26.3%
Missing1
Missing (%)0.1%
Memory size59.8 KiB
2023-12-09T22:31:25.563653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.167167167
Min length1

Characters and Unicode

Total characters4163
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)17.3%

Sample

1st row0
2nd row2460.1
3rd row318.6
4th row0
5th row287.7
ValueCountFrequency (%)
0 136
 
13.6%
225 85
 
8.5%
325 61
 
6.1%
308.3 32
 
3.2%
246.5 31
 
3.1%
236.2 31
 
3.1%
318.6 22
 
2.2%
195 22
 
2.2%
267.1 21
 
2.1%
339.2 18
 
1.8%
Other values (253) 540
54.1%
2023-12-09T22:31:26.091323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 668
16.0%
. 634
15.2%
5 441
10.6%
3 430
10.3%
1 387
9.3%
0 342
8.2%
9 271
6.5%
6 268
6.4%
4 260
 
6.2%
7 238
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3529
84.8%
Other Punctuation 634
 
15.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 668
18.9%
5 441
12.5%
3 430
12.2%
1 387
11.0%
0 342
9.7%
9 271
7.7%
6 268
7.6%
4 260
 
7.4%
7 238
 
6.7%
8 224
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 634
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4163
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 668
16.0%
. 634
15.2%
5 441
10.6%
3 430
10.3%
1 387
9.3%
0 342
8.2%
9 271
6.5%
6 268
6.4%
4 260
 
6.2%
7 238
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 668
16.0%
. 634
15.2%
5 441
10.6%
3 430
10.3%
1 387
9.3%
0 342
8.2%
9 271
6.5%
6 268
6.4%
4 260
 
6.2%
7 238
 
5.7%
Distinct267
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size59.9 KiB
2023-12-09T22:31:26.461980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.182
Min length1

Characters and Unicode

Total characters4182
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)17.7%

Sample

1st row0
2nd row2460.1
3rd row318.6
4th row0
5th row287.7
ValueCountFrequency (%)
0 136
 
13.6%
225 85
 
8.5%
325 61
 
6.1%
308.3 32
 
3.2%
246.5 31
 
3.1%
236.2 31
 
3.1%
318.6 22
 
2.2%
195 22
 
2.2%
267.1 21
 
2.1%
339.2 18
 
1.8%
Other values (257) 541
54.1%
2023-12-09T22:31:26.960378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 664
15.9%
. 640
15.3%
5 447
10.7%
3 436
10.4%
1 388
9.3%
0 335
8.0%
9 271
6.5%
6 269
6.4%
4 264
 
6.3%
7 241
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3542
84.7%
Other Punctuation 640
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 664
18.7%
5 447
12.6%
3 436
12.3%
1 388
11.0%
0 335
9.5%
9 271
7.7%
6 269
7.6%
4 264
 
7.5%
7 241
 
6.8%
8 227
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 640
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4182
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 664
15.9%
. 640
15.3%
5 447
10.7%
3 436
10.4%
1 388
9.3%
0 335
8.0%
9 271
6.5%
6 269
6.4%
4 264
 
6.3%
7 241
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4182
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 664
15.9%
. 640
15.3%
5 447
10.7%
3 436
10.4%
1 388
9.3%
0 335
8.0%
9 271
6.5%
6 269
6.4%
4 264
 
6.3%
7 241
 
5.8%

amount_due
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2023-12-09T22:31:27.078264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1000
100.0%
2023-12-09T22:31:27.300520image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1000
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1000
100.0%
Distinct847
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size64.5 KiB
2023-12-09T22:31:27.657355image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.903
Min length7

Characters and Unicode

Total characters8903
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique746 ?
Unique (%)74.6%

Sample

1st row40.657723
2nd row40.748276
3rd row40.750353
4th row40.757792
5th row40.773397
ValueCountFrequency (%)
40.758754 9
 
0.9%
40.751604 8
 
0.8%
40.75785 7
 
0.7%
40.754074 6
 
0.6%
40.696809 5
 
0.5%
40.726168 4
 
0.4%
40.752732 4
 
0.4%
40.733812 4
 
0.4%
40.756456 4
 
0.4%
40.758828 4
 
0.4%
Other values (837) 945
94.5%
2023-12-09T22:31:28.167040image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1496
16.8%
0 1377
15.5%
7 1145
12.9%
. 1000
11.2%
6 708
8.0%
5 665
7.5%
8 619
7.0%
3 511
 
5.7%
2 499
 
5.6%
9 457
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7903
88.8%
Other Punctuation 1000
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1496
18.9%
0 1377
17.4%
7 1145
14.5%
6 708
9.0%
5 665
8.4%
8 619
7.8%
3 511
 
6.5%
2 499
 
6.3%
9 457
 
5.8%
1 426
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8903
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1496
16.8%
0 1377
15.5%
7 1145
12.9%
. 1000
11.2%
6 708
8.0%
5 665
7.5%
8 619
7.0%
3 511
 
5.7%
2 499
 
5.6%
9 457
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8903
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1496
16.8%
0 1377
15.5%
7 1145
12.9%
. 1000
11.2%
6 708
8.0%
5 665
7.5%
8 619
7.0%
3 511
 
5.7%
2 499
 
5.6%
9 457
 
5.1%
Distinct845
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size65.4 KiB
2023-12-09T22:31:28.559889image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.89
Min length8

Characters and Unicode

Total characters9890
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique743 ?
Unique (%)74.3%

Sample

1st row-73.940499
2nd row-73.98469
3rd row-73.945927
4th row-73.861757
5th row-73.957292
ValueCountFrequency (%)
73.978692 9
 
0.9%
73.997932 8
 
0.8%
73.97348 7
 
0.7%
73.999513 6
 
0.6%
73.936674 5
 
0.5%
73.975193 4
 
0.4%
73.973978 4
 
0.4%
74.007494 4
 
0.4%
73.982727 4
 
0.4%
73.988435 4
 
0.4%
Other values (835) 945
94.5%
2023-12-09T22:31:29.088901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1612
16.3%
3 1378
13.9%
9 1291
13.1%
- 1000
10.1%
. 1000
10.1%
8 748
7.6%
4 606
 
6.1%
5 477
 
4.8%
6 463
 
4.7%
2 453
 
4.6%
Other values (2) 862
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7890
79.8%
Dash Punctuation 1000
 
10.1%
Other Punctuation 1000
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1612
20.4%
3 1378
17.5%
9 1291
16.4%
8 748
9.5%
4 606
 
7.7%
5 477
 
6.0%
6 463
 
5.9%
2 453
 
5.7%
0 440
 
5.6%
1 422
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 1000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9890
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1612
16.3%
3 1378
13.9%
9 1291
13.1%
- 1000
10.1%
. 1000
10.1%
8 748
7.6%
4 606
 
6.1%
5 477
 
4.8%
6 463
 
4.7%
2 453
 
4.6%
Other values (2) 862
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1612
16.3%
3 1378
13.9%
9 1291
13.1%
- 1000
10.1%
. 1000
10.1%
8 748
7.6%
4 606
 
6.1%
5 477
 
4.8%
6 463
 
4.7%
2 453
 
4.6%
Other values (2) 862
8.7%
Distinct19
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size56.9 KiB
2023-12-09T22:31:29.257378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.179
Min length1

Characters and Unicode

Total characters1179
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row5
3rd row2
4th row3
5th row8
ValueCountFrequency (%)
5 209
20.9%
2 116
11.6%
6 95
9.5%
7 90
9.0%
1 75
 
7.5%
4 74
 
7.4%
8 72
 
7.2%
12 56
 
5.6%
3 53
 
5.3%
9 37
 
3.7%
Other values (9) 123
12.3%
2023-12-09T22:31:29.522823image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 285
24.2%
5 217
18.4%
2 172
14.6%
6 102
 
8.7%
7 98
 
8.3%
4 95
 
8.1%
8 79
 
6.7%
3 62
 
5.3%
9 37
 
3.1%
0 32
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1179
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 285
24.2%
5 217
18.4%
2 172
14.6%
6 102
 
8.7%
7 98
 
8.3%
4 95
 
8.1%
8 79
 
6.7%
3 62
 
5.3%
9 37
 
3.1%
0 32
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1179
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 285
24.2%
5 217
18.4%
2 172
14.6%
6 102
 
8.7%
7 98
 
8.3%
4 95
 
8.1%
8 79
 
6.7%
3 62
 
5.3%
9 37
 
3.1%
0 32
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1179
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 285
24.2%
5 217
18.4%
2 172
14.6%
6 102
 
8.7%
7 98
 
8.3%
4 95
 
8.1%
8 79
 
6.7%
3 62
 
5.3%
9 37
 
3.1%
0 32
 
2.7%
Distinct49
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size57.2 KiB
2023-12-09T22:31:29.727539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.407
Min length1

Characters and Unicode

Total characters1407
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row40
2nd row4
3rd row26
4th row21
5th row4
ValueCountFrequency (%)
4 213
21.3%
3 127
 
12.7%
1 76
 
7.6%
2 52
 
5.2%
6 41
 
4.1%
33 33
 
3.3%
5 30
 
3.0%
26 29
 
2.9%
10 26
 
2.6%
29 20
 
2.0%
Other values (39) 353
35.3%
2023-12-09T22:31:30.054930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 330
23.5%
3 287
20.4%
1 222
15.8%
2 170
12.1%
6 98
 
7.0%
5 72
 
5.1%
0 64
 
4.5%
9 61
 
4.3%
8 57
 
4.1%
7 46
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1407
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 330
23.5%
3 287
20.4%
1 222
15.8%
2 170
12.1%
6 98
 
7.0%
5 72
 
5.1%
0 64
 
4.5%
9 61
 
4.3%
8 57
 
4.1%
7 46
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1407
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 330
23.5%
3 287
20.4%
1 222
15.8%
2 170
12.1%
6 98
 
7.0%
5 72
 
5.1%
0 64
 
4.5%
9 61
 
4.3%
8 57
 
4.1%
7 46
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 330
23.5%
3 287
20.4%
1 222
15.8%
2 170
12.1%
6 98
 
7.0%
5 72
 
5.1%
0 64
 
4.5%
9 61
 
4.3%
8 57
 
4.1%
7 46
 
3.3%
Distinct374
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Memory size58.6 KiB
2023-12-09T22:31:30.540828image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.879
Min length1

Characters and Unicode

Total characters2879
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)19.1%

Sample

1st row808
2nd row76
3rd row19
4th row381
5th row134
ValueCountFrequency (%)
99 21
 
2.1%
104 21
 
2.1%
100 17
 
1.7%
37 15
 
1.5%
102 15
 
1.5%
131 15
 
1.5%
125 14
 
1.4%
92 13
 
1.3%
94 13
 
1.3%
7 13
 
1.3%
Other values (364) 843
84.3%
2023-12-09T22:31:31.147690image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 622
21.6%
2 334
11.6%
0 321
11.1%
9 287
10.0%
3 279
9.7%
4 249
8.6%
5 225
 
7.8%
7 211
 
7.3%
8 179
 
6.2%
6 172
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2879
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 622
21.6%
2 334
11.6%
0 321
11.1%
9 287
10.0%
3 279
9.7%
4 249
8.6%
5 225
 
7.8%
7 211
 
7.3%
8 179
 
6.2%
6 172
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2879
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 622
21.6%
2 334
11.6%
0 321
11.1%
9 287
10.0%
3 279
9.7%
4 249
8.6%
5 225
 
7.8%
7 211
 
7.3%
8 179
 
6.2%
6 172
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2879
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 622
21.6%
2 334
11.6%
0 321
11.1%
9 287
10.0%
3 279
9.7%
4 249
8.6%
5 225
 
7.8%
7 211
 
7.3%
8 179
 
6.2%
6 172
 
6.0%

bbl
Text

Distinct810
Distinct (%)81.8%
Missing10
Missing (%)1.0%
Memory size65.2 KiB
2023-12-09T22:31:31.464092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters9900
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique700 ?
Unique (%)70.7%

Sample

1st row3048120001
2nd row1008350041
3rd row4004420028
4th row4017220001
5th row1014330007
ValueCountFrequency (%)
1012657501 9
 
0.9%
1007290051 8
 
0.8%
1013060001 7
 
0.7%
1012770027 6
 
0.6%
2036370001 6
 
0.6%
1007050039 6
 
0.6%
1009720001 6
 
0.6%
3015860012 5
 
0.5%
1012880027 4
 
0.4%
1005790047 4
 
0.4%
Other values (800) 929
93.8%
2023-12-09T22:31:31.896461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3786
38.2%
1 1793
18.1%
2 790
 
8.0%
3 731
 
7.4%
5 605
 
6.1%
7 550
 
5.6%
4 523
 
5.3%
6 388
 
3.9%
9 370
 
3.7%
8 364
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9900
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3786
38.2%
1 1793
18.1%
2 790
 
8.0%
3 731
 
7.4%
5 605
 
6.1%
7 550
 
5.6%
4 523
 
5.3%
6 388
 
3.9%
9 370
 
3.7%
8 364
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 9900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3786
38.2%
1 1793
18.1%
2 790
 
8.0%
3 731
 
7.4%
5 605
 
6.1%
7 550
 
5.6%
4 523
 
5.3%
6 388
 
3.9%
9 370
 
3.7%
8 364
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3786
38.2%
1 1793
18.1%
2 790
 
8.0%
3 731
 
7.4%
5 605
 
6.1%
7 550
 
5.6%
4 523
 
5.3%
6 388
 
3.9%
9 370
 
3.7%
8 364
 
3.7%
Distinct139
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size77.0 KiB
2023-12-09T22:31:32.270972image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length48
Median length39
Mean length21.738
Min length7

Characters and Unicode

Total characters21738
Distinct characters52
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)3.4%

Sample

1st rowProspect Lefferts Gardens-Wingate
2nd rowMidtown-Midtown South
3rd rowHunters Point-Sunnyside-West Maspeth
4th rowNorth Corona
5th rowLenox Hill-Roosevelt Island
ValueCountFrequency (%)
south 200
 
8.3%
midtown-midtown 157
 
6.5%
east 96
 
4.0%
square 85
 
3.5%
west 81
 
3.4%
village 69
 
2.9%
park 67
 
2.8%
heights 64
 
2.7%
hudson 61
 
2.5%
yards-chelsea-flatiron-union 61
 
2.5%
Other values (186) 1461
60.8%
2023-12-09T22:31:32.805909image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1743
 
8.0%
o 1575
 
7.2%
e 1567
 
7.2%
1402
 
6.4%
i 1381
 
6.4%
n 1365
 
6.3%
a 1306
 
6.0%
r 1142
 
5.3%
l 997
 
4.6%
s 954
 
4.4%
Other values (42) 8306
38.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16067
73.9%
Uppercase Letter 3409
 
15.7%
Space Separator 1402
 
6.4%
Dash Punctuation 854
 
3.9%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1743
10.8%
o 1575
9.8%
e 1567
9.8%
i 1381
8.6%
n 1365
8.5%
a 1306
8.1%
r 1142
 
7.1%
l 997
 
6.2%
s 954
 
5.9%
d 776
 
4.8%
Other values (15) 3261
20.3%
Uppercase Letter
ValueCountFrequency (%)
M 487
14.3%
S 473
13.9%
H 383
11.2%
C 356
10.4%
B 268
 
7.9%
E 161
 
4.7%
W 148
 
4.3%
U 134
 
3.9%
P 130
 
3.8%
F 124
 
3.6%
Other values (14) 745
21.9%
Space Separator
ValueCountFrequency (%)
1402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 854
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19476
89.6%
Common 2262
 
10.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1743
 
8.9%
o 1575
 
8.1%
e 1567
 
8.0%
i 1381
 
7.1%
n 1365
 
7.0%
a 1306
 
6.7%
r 1142
 
5.9%
l 997
 
5.1%
s 954
 
4.9%
d 776
 
4.0%
Other values (39) 6670
34.2%
Common
ValueCountFrequency (%)
1402
62.0%
- 854
37.8%
. 6
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21738
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1743
 
8.0%
o 1575
 
7.2%
e 1567
 
7.2%
1402
 
6.4%
i 1381
 
6.4%
n 1365
 
6.3%
a 1306
 
6.0%
r 1142
 
5.3%
l 997
 
4.6%
s 954
 
4.4%
Other values (42) 8306
38.2%